WO2016081339A1 - Surveillance de conformité de traitement à l'aide de formes de parole capturées passivement à partir d'un environnement de patient - Google Patents

Surveillance de conformité de traitement à l'aide de formes de parole capturées passivement à partir d'un environnement de patient Download PDF

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Publication number
WO2016081339A1
WO2016081339A1 PCT/US2015/060803 US2015060803W WO2016081339A1 WO 2016081339 A1 WO2016081339 A1 WO 2016081339A1 US 2015060803 W US2015060803 W US 2015060803W WO 2016081339 A1 WO2016081339 A1 WO 2016081339A1
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WO
WIPO (PCT)
Prior art keywords
patient
speech
signal
speech data
treatment regimen
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/US2015/060803
Other languages
English (en)
Inventor
Jeffrey A. Bowers
Paul Duesterhoft
Daniel Hawkins
Roderick A. Hyde
Edward K.Y. Jung
Jordin T. Kare
Eric C. Leuthardt
Nathan P. Myhrvold
Michael A. Smith
Elizabeth A. Sweeney
Clarence T. Tegreene
Lowell L. Wood, Jr.
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Elwha LLC
Original Assignee
Elwha LLC
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from US14/543,066 external-priority patent/US9585616B2/en
Priority claimed from US14/543,030 external-priority patent/US9589107B2/en
Application filed by Elwha LLC filed Critical Elwha LLC
Priority to HK18102865.8A priority Critical patent/HK1243519A1/zh
Priority to EP15861246.5A priority patent/EP3221839A4/fr
Priority to CN201580062375.3A priority patent/CN107111672A/zh
Publication of WO2016081339A1 publication Critical patent/WO2016081339A1/fr
Priority to IL252279A priority patent/IL252279A0/en
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/10—Office automation; Time management
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
    • G16H10/65—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records stored on portable record carriers, e.g. on smartcards, RFID tags or CD
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
    • G16H40/67—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/48—Other medical applications
    • A61B5/4833—Assessment of subject's compliance to treatment
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/22—Social work or social welfare, e.g. community support activities or counselling services
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L17/00—Speaker identification or verification techniques
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
    • G10L25/48—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use
    • G10L25/51—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use for comparison or discrimination
    • G10L25/66—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use for comparison or discrimination for extracting parameters related to health condition
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H70/00—ICT specially adapted for the handling or processing of medical references
    • G16H70/20—ICT specially adapted for the handling or processing of medical references relating to practices or guidelines

Definitions

  • a system for monitoring compliance of a patient with a prescribed treatment regimen includes, but is not limited to, at least one receiving device for use at a monitoring location for receiving a speech data signal transmitted to the monitoring location from a patient location, the speech data signal containing speech data, the speech data including patient speech data representing spontaneous speech sensed from a patient with at least one audio sensor at the patient location, and the patient having a brain-related disorder and a prescribed treatment regimen for treating at least one aspect of the brain- related disorder; speech identification circuitry configured to identify the patient speech data corresponding to speech from the patient in the speech data, the patient speech data including data indicative of at least one patient speech pattern; compliance determination circuitry configured to determine compliance of the patient with the prescribed treatment regimen based on whether the patient speech data includes data indicative of the at least one patient speech pattern matching at least one characteristic speech pattern; and reporting circuitry configured to report a conclusion based on the determination of whether the patient has complied with the prescribed treatment regimen.
  • a method of monitoring compliance of a patient with a prescribed treatment regimen includes, but is not limited to, receiving a speech data signal with a receiving device at a monitoring location, the speech data signal transmitted to the monitoring location from a patient location, the speech data signal containing speech data, the speech data including patient speech data representing spontaneous speech sensed from a patient by at least one audio sensor at the patient location, and the patient having a brain-related disorder and a prescribed treatment regimen for treating at least one aspect of the brain-related disorder, identifying with speech identification circuitry patient speech data corresponding to speech from the patient in the speech data, the patient speech data including data indicative of at least one patient speech pattern, determining with compliance determination circuitry whether the patient has complied with the prescribed treatment regimen based on whether the patient speech data includes data indicative of the at least one patient speech pattern matching at least one characteristic speech pattern, and reporting with reporting circuitry a conclusion based on the determination of whether the patient has complied with the prescribed treatment regimen.
  • a computer program product includes, but is not limited to, a non- transitory signal-bearing medium bearing one or more instructions for one or more instructions for receiving a speech data signal with a receiving device at a monitoring location, the speech data signal transmitted to the monitoring location from a patient location, the speech data signal containing speech data, the speech data including patient speech data representing spontaneous speech sensed from a patient by at least one audio sensor at a patient location, and the patient having a brain-related disorder and a prescribed treatment regimen for treating at least one aspect of the brain-related disorder; one or more instructions for identifying with speech identification circuitry patient speech data corresponding to speech from the patient in the speech data, the patient speech data including data indicative of at least one patient speech pattern; one or more instructions for determining with compliance determination circuitry whether the patient has complied with the prescribed treatment regimen based on whether the patient speech data includes data indicative of the at least one patient speech pattern matching at least one
  • a system includes, but is not limited to, a computing device and instructions that when executed on the computing device cause the computing device to receive a speech data signal with a receiving device at a monitoring location, the speech data signal transmitted to the monitoring location from a patient location, the speech data signal containing speech data, the speech data including patient speech data representing spontaneous speech sensed from a patient by at least one audio sensor at a patient location, and the patient having a brain-related disorder and a prescribed treatment regimen for treating at least one aspect of the brain-related disorder; identify with speech identification circuitry patient speech data corresponding to speech from the patient in the speech data, the patient speech data including data indicative of at least one patient speech pattern; determine with compliance determination circuitry whether the patient has complied with the prescribed treatment regimen based on whether the patient speech data includes data indicative of the at least one patient speech pattern matching at least one characteristic speech pattern; and report with reporting circuitry a conclusion based on the determination of whether the patient has complied with the prescribed treatment regimen.
  • other aspects of a computing device include, but is not limited to,
  • a system for monitoring compliance of a patient with a treatment regimen includes, but is not limited to, at least one audio sensor for sensing at least one audio signal including spontaneous speech from a patient at a patient location, the patient having a brain-related disorder and a prescribed treatment regimen for treating at least one aspect of the brain-related disorder, signal processing circuitry for detecting the spontaneous speech in the at least one audio signal and generating speech data including data indicative of whether the patient has complied with the prescribed treatment regimen based upon the detected spontaneous speech, and at least one transmitting device for transmitting a speech data signal containing the speech data including data indicative of whether the patient has complied with the prescribed treatment regimen from the patient location to a receiving device at a monitoring location.
  • the signal processing circuitry includes patient identification circuitry configured to determine a presence of the patient from at least one identity signal sensed at the patient location, wherein the signal processing circuitry is configured to detect the spontaneous speech from the patient based at least in part on the determination of the presence of the patient by the patient identification circuitry.
  • a method includes, but is not limited to, sensing at least one audio signal including spontaneous speech from a patient with at least one audio sensor at a patient location, the patient having a brain-related disorder and a prescribed treatment regimen for treating at least one aspect of the brain-related disorder, detecting the spontaneous speech of the patient in the at least one audio signal with signal processing circuitry at the patient location, generating with the signal processing circuitry speech data including data indicative of whether the patient has complied with the prescribed treatment regimen, and transmitting a speech data signal containing the speech data including data indicative of whether the patient has complied with the prescribed treatment regimen to a receiving device at a monitoring location with at least one transmitting device at the patient location.
  • the method includes determining a presence of the patient with patient identification circuitry based on at least one identity signal sensed at the patient location, wherein detecting spontaneous speech of the patient in the at least one audio signal with the signal processing circuitry at the patient location includes detecting speech from the patient based at least in part on the determination of the presence of the patient by the patient identification circuitry.
  • a computer program product includes, but is not limited to, a non- transitory signal-bearing medium bearing one or more instructions for sensing at least one audio signal including spontaneous speech from a patient with at least one audio sensor at a patient location, the patient having a brain-related disorder and a prescribed treatment regimen for treating at least one aspect of the brain-related disorder, one or more instructions for detecting the spontaneous speech of the patient in the at least one audio signal with signal processing circuitry at the patient location, one or more instructions for generating with the signal processing circuitry speech data including data indicative of whether the patient has complied with the prescribed treatment regimen; and one or more instructions for transmitting a speech data signal containing the speech data including data indicative of whether speech data including data indicative of whether the patient has complied with the prescribed treatment regimen to a receiving device at a monitoring location with at least one transmitting device at the patient location.
  • the non-transitory signal -bearing medium bears one or more instructions for determining a presence of the patient with the patient identification circuitry based on at least one identity signal sensed at the patient location, wherein detecting the spontaneous speech of the patient in the at least one audio signal with the signal processing circuitry at the patient location includes detecting speech from the patient based at least in part on the
  • a system includes, but is not limited to, a computing device and instructions that when executed on the computing device cause the computing device to sense at least one audio signal including spontaneous speech from a patient with at least one audio sensor at a patient location, the patient having a brain-related disorder and a prescribed treatment regimen for treating at least one aspect of the brain-related disorder, detect the spontaneous speech of the patient in the at least one audio signal with signal processing circuitry at the patient location, generate with the signal processing circuitry speech data including data indicative whether the patient has complied with the prescribed treatment regimen, and transmit a speech data signal containing the speech data including data indicative of whether the patient has complied with the prescribed treatment regimen to a receiving device at a monitoring location with at least one transmitting device at the patient location.
  • FIG. 1 is a block diagram of a system for monitoring compliance of a patient with a prescribed treatment regimen.
  • FIG. 2 is a block diagram of components of a system for monitoring compliance of a patient with a prescribed treatment regimen at a patient location.
  • FIG. 3 is a block diagram of components a system for monitoring compliance of a patient with a prescribed treatment regimen at a monitoring location.
  • FIG. 4 illustrates an embodiment of a system for monitoring compliance of a patient with a prescribed treatment regimen.
  • FIG. 5 illustrates another embodiment of a system for monitoring compliance of a patient with a prescribed treatment regimen.
  • FIG. 6 illustrates another embodiment of a system for monitoring compliance of a patient with a prescribed treatment regimen.
  • FIG. 7 illustrates another embodiment of a system for monitoring compliance of a patient with a prescribed treatment regimen.
  • FIG. 8 is a generalized system block diagram.
  • FIG. 9 is a flow diagram of a method of monitoring compliance of patient with a prescribed treatment regimen.
  • FIG. 10 is a flow diagram of further aspects of the method of FIG. 9.
  • FIG. 11 is a flow diagram of further aspects of the method of FIG. 9.
  • FIG. 12 is a flow diagram of further aspects of the method of FIG. 9.
  • FIG. 13 is a flow diagram of further aspects of the method of FIG. 9.
  • FIG. 14 is a flow diagram of further aspects of the method of FIG. 9.
  • FIG. 15 is a flow diagram of further aspects of the method of FIG. 9.
  • FIG. 16 is a flow diagram of further aspects of the method of FIG. 9.
  • FIG. 17 is a flow diagram of further aspects of the method of FIG. 9.
  • FIG. 18 is a flow diagram of further aspects of the method of FIG. 9.
  • FIG. 19 is a block diagram of a computer program product including a signal bearing medium.
  • FIG. 20 is a block diagram of a system including a computing device.
  • FIG. 21 is a flow diagram of a method of monitoring compliance of patient with prescribed treatment regimen.
  • FIG. 22 is a flow diagram of further aspects of the method of FIG. 22.
  • FIG. 23 is a flow diagram of further aspects of the method of FIG. 22.
  • FIG. 24 is a flow diagram of further aspects of the method of FIG. 22.
  • FIG. 25 is a flow diagram of further aspects of the method of FIG. 22.
  • FIG. 26 is a flow diagram of further aspects of the method of FIG. 22.
  • FIG. 27 is a flow diagram of further aspects of the method of FIG. 22.
  • FIG. 28 is a flow diagram of further aspects of the method of FIG. 22.
  • FIG. 29 is a flow diagram of further aspects of the method of FIG. 22.
  • FIG. 30 is a flow diagram of further aspects of the method of FIG. 22.
  • FIG. 31 is a flow diagram of further aspects of the method of FIG. 22.
  • FIG. 32 is a flow diagram of further aspects of the method of FIG. 22.
  • FIG. 33 is a block diagram of a computer program product including a signal- bearing medium.
  • FIG. 34 is a block diagram of a system including a computing device.
  • FIG. 1 illustrates a system 100 for monitoring compliance of a patient 102 with a prescribed treatment regimen 104.
  • patient 102 has a brain-related disorder
  • prescribed treatment regimen 104 is a treatment regimen prescribed to patient 102 for treating at least one aspect of the brain-related disorder.
  • Brain-related disorders include, for example, mental disorders, psychological disorders, psychiatric disorder, traumatic disorders, lesion-related disorders, and/or neurological disorders, as discussed in greater detail herein below.
  • Prescribed treatment regimen 104 may include a prescription for one or more therapeutic treatments, including medications, pharmaceuticals, nutraceuticals, therapeutic activities, diet, sleep, exercise, counseling, etc., to be used individually or in combination.
  • prescribed treatment regimen 104 specifies type, quantity, and time course of any or all such therapeutic treatments.
  • System 100 monitors compliance of patient 102 with a prescribed treatment regimen 104 by detecting and analyzing speech 120 from patient 102.
  • speech 120 is processed by local system 106, and speech data signal 128 is transmitted to monitoring location 112, and a conclusion 149 (e.g., regarding patient's compliance or lack thereof) reported to medical care provider 151.
  • Systems as described herein can be used, for example, to monitor patient compliance with a prescribed treatment regimen at the request of or with the cooperation and/or authorization of the patient, e.g., in the situation that the patient and/or the patient's caregiver wish to track the patient's compliance with the prescribed treatment regimen.
  • monitoring of patient compliance with a prescribed treatment regimen can be implemented at the request or requirement of a caregiver, insurance company, or other individual or entity, for example, as a condition of living in a group home, mental health care facility, or other institution.
  • monitoring of compliance can be implemented without knowledge and/or authorization of the patient, e.g., in situations in which the patient is not capable of making decisions for his or her self or to fulfill a legal requirement.
  • System 100 includes local system 106 at patient location 108, and monitoring system 110 at monitoring location 112.
  • patient location 108 includes, but is not limited, to the patient's home, workplace, school, medical care facility, or group home, or the vicinity of a mobile or stationary device used by the patient, e.g., a cell phone or computer.
  • Local system 106 includes at least one audio sensor 114 for sensing at least one audio signal 116 including spontaneous speech 120 from patient 102 at patient location 108.
  • Local system 106 also includes signal processing circuitry 122 for detecting spontaneous speech 120 in the at least one audio signal 116 and generating speech data 124 indicative of whether the patient has complied with the prescribed treatment regimen based upon the detected spontaneous speech 120.
  • Spontaneous speech refers to speech that is produced independent of any prompt by system 100, and includes, for example, free-flowing or natural speech. Such speech can be considered "passively captured" from the patient environment in that capture of the spontaneous speech is not predicated on the delivery of a prompt to the patient from system 100.
  • spontaneous speech in some cases includes speech produced by the patient in response to prompts or queries by another person, e.g., in the course of interaction with one or more other person.
  • speech produced by the patient that is not dependent on prior interaction with another person is also considered "spontaneous speech.”
  • speech includes coherent speech, incoherent speech, singing, shouting, whispering, crying, chanting, or other verbal or non-verbal vocalizations.
  • Local system 106 also includes at least one transmitting device 126 for transmitting speech data signal 128 containing speech data 124, which includes indicative of whether patient 102 has complied with the prescribed treatment regimen from patient location 108 to receiving device 130 at a monitoring location 112.
  • Local system 106 may include or be
  • System 100 includes monitoring system 110, which is used at monitoring location
  • Monitoring system 110 allows medical care provider 151 to remotely monitor compliance of patient 102 with prescribed treatment regimen 104.
  • Monitoring location 112 may be, for example, a hospital, clinic, data center, or doctor's office. Monitoring location 112 may be a short distance away from patient location 108 (e.g., in another room of the same building, or even within the same room as patient location 108) or it may be in a separate building, a few miles away, or many miles away.
  • Monitoring system 110 includes at least one receiving device 130 for use at monitoring location 112 for receiving speech data signal 128 transmitted to monitoring location 112 from patient locationl08. Speech data signal 128 contains speech data 124, which may include patient speech data 136.
  • patient speech data 136 represents spontaneous speech sensed from patient 102 with at least one audio sensor 114 at patient location 108.
  • Monitoring system 110 includes speech identification circuitry 140 configured to identify patient speech data 136 corresponding to speech from the patient in speech data 124, where patient speech data 136 is indicative of at least one patient speech pattern 142.
  • Monitoring system 110 also includes compliance determination circuitry 144, which is configured to determine compliance of patient 102 with prescribed treatment regimen 104 based on whether patient speech data 124 is indicative of at least one patient speech pattern 142 matching at least one characteristic speech pattern 146.
  • Monitoring system 110 also includes reporting circuitry 148 configured to report a conclusion 149 based on the determination of whether patient 102 has complied with prescribed treatment regimen 104. In an aspect, conclusion 149 is reported to medical care provider 151 or other appropriate party.
  • FIG. 2 provides greater detail regarding local system 106 at patient location 108.
  • Local system 106 can be constructed and implemented in a variety of embodiments in which different devices and/or device components provide the functionality described herein.
  • audio sensor 114, signal processing circuitry 122, and transmitting device 126 may be components of a cell phone configured with application software, as indicated at 180; a computing system or device 182; a data streaming device 184; or a stand-alone microprocessor-based device 186; examples of which are shown in FIGS. 4 - 7.
  • audio sensor 114 includes microphone 172.
  • Local system 106 may include one or multiple audio sensors 114, which may be of the same or different types, without limitation, and one or more transmitting device 126. Audio sensor 114 may include built-in components (e.g., of cell phone 180, or stand-alone microprocessor-based device 186) or separate components connected to, e.g., a computing system 182 or cell phone 180 via a wired or wireless connection.
  • local system 106 includes one or more data storage device 200, which may be any of various types of data storage and/or memory devices.
  • Local system 106 may include one or more power source (not shown), e.g., a battery, a plug for connecting to an electrical outlet or USB port, or any of various other types of power sources.
  • Local system 106 includes transmitting device 126, which in various aspects includes a wireless transmitter 230, which may be configured to transmit to a wireless router 232 or cellular network 234, for example.
  • transmitting device 126 includes a computer network connection 236, e.g., an Ethernet connection 238, or a hardware connection 240, for example a USB port 242 or computer drive 246.
  • Transmitting device 126 functions to transmit speech data signal 128, but may also be used to transmit notification 270 generated by notification circuitry 250, identity signal 302, and other data, instructions, or information, for example as discussed elsewhere herein.
  • transmitting device 126 forms a part of communication circuitry 284, which provides for two-way communication between local system 106 and the monitoring system (e.g., monitoring system 110 as shown in FIG. 1), and one-way or two- way communication between local system 106 and other systems or devices located remotely from local system 106.
  • local system 106 includes notification circuitry 250 for generating a notification.
  • a notification includes any messages or alerts provided to patient 102, medical care provider 151, or other interested parties (e.g., family of patient 102), including but not limited to messages regarding operation of local system 106 or patient compliance, for example.
  • Notifications may take the form of standard messages, a number of which may be stored in data storage device 200.
  • a notification could be a message to patient 102 stating "Reminder: Take your medication” or a message to a medical care provider stating "Alert: Patient xxx speech pattern indicates noncompliance with treatment regimen.”
  • Generation of a notification includes retrieval of all or a portion of a message from data storage device 200.
  • notification circuitry 250 includes at least one of email generation circuitry 252 for generating an email notification, wireless notification circuitry 254 for generating a notification to be transmitted via a wireless transmitter (e.g., wireless transmitter 230), and notification storage circuitry 256 for storing a notification in a data storage device (e.g., data storage device 200). In some cases, notifications may be stored for later retrieval or transmittal to a monitoring location. Notification 270 generated by notification circuitry 250 can be transmitted by signal processing circuitry 122.
  • speech data signal 128 transmitted to monitoring system 110 contains processed data. In some cases a determination of whether patient 102 has complied with prescribed treatment regimen 104 is made by local system 106. In some cases speech data signal 128 transmitted to monitoring location 112 includes speech data that has not been subjected to significant processing, and speech processing and detection of patient compliance is performed at monitoring location 112. In an aspect, speech data is stored for later processing, e.g., in data storage device 200 in local system 106, or is subjected to processing but also stored for later transfer to monitoring location 112.
  • Signal processing circuitry 122 is used for detecting spontaneous speech 120 in the at least one audio signal 116 and generating speech data 124 including data indicative of whether the patient has complied with the prescribed treatment regimen based upon the detected spontaneous speech 120.
  • speech data including data indicative of whether the patient has complied with the prescribed treatment regimen means speech data that includes informative speech data, i.e., speech data from which it may be determined that the patient complied with the prescribed treatment regimen.
  • Speech data including data indicative of whether the patient has complied with the prescribed treatment regimen may, in addition to informative speech data, include non-informative speech data, i.e., speech data that does not provide any information regarding, and from which it cannot be determined, whether the patient complied with the prescribed treatment regimen.
  • speech data may refer to any or all of a digitized audio signal containing one or more speech-containing portions and one or more non-speech- containing portions, a digitized audio signal from which non-speech-containing portions have been removed to leave one or more speech-containing portions, speech pattern data derived or computed from a digitized audio signal containing speech, or speech parameter data derived or computed from a digitized audio signal containing speech, for example.
  • speech data may include several types of data, e.g., one or more digitized audio signal, one or more speech pattern, and/or one or more speech parameter.
  • signal processing circuitry 122 includes speech processor 202.
  • speech processor 202 is configured to process the at least one audio signal 116 to identify at least one portion of the at least one audio signal 116 containing spontaneous speech of the patient.
  • speech processor 202 is configured to process at least one audio signal 116 to exclude at least one portion of at least one audio signal 116 that does not contain spontaneous speech of the patient.
  • speech data 124 includes the at least one section of the at least one audio signal 116 containing spontaneous speech of the patient.
  • speech processor 202 is configured to process at least one audio signal 116 to determine at least one speech pattern 142 of the patient.
  • speech data 124 includes the at least one speech pattern 142 of the patient.
  • a speech pattern can be defined as a consistent, characteristic form, style, or method of speech comprising a distribution or arrangement of repeated or corresponding parts composed of qualities, acts, or tendencies.
  • a speech pattern can include one or more qualities of diction, elocution, inflection, and/or intonation.
  • a speech pattern can include aspects of language at the lexical level, sentential level, or discourse level.
  • a speech pattern may conform to the Thought, Language, and Communication Scale and/or Thought and Language Index. Reviews describing speech patterns and linguistic levels and the tools used to study them include Covington M.A., et al. "Schizophrenia and the structure of language: The linguist's view," Schizophrenia Research 77: 85-98, 2005, and Kuperberg and Caplan (2003 Book Chapter: Language Dysfunction in Schizophrenia), which are both
  • a speech pattern includes a linguistic pattern determined at the lexical level.
  • a speech pattern may include a frequency of, for example, pauses, words, or phrases.
  • a speech pattern may include a frequency of pauses.
  • a higher frequency of pauses or reduced verbal fluency can be indicative of alogia associated with a brain disorder, e.g., bipolar disorder, depression, or schizophrenia.
  • a speech pattern may include a frequency of dysfluencies ("uhs" and "urns"). A higher than average frequency of dysfluencies may indicate a slowed speech, the inability to think clearly, or a deliberate attempt to appear unaffected by illness, all of which have been associated with psychological pathologies.
  • a speech pattern may include a distribution of pauses and dysfluencies.
  • a high frequency and particular distribution of pauses and dysfluencies may be indicative of anomia associated with schizophrenia or with an aphasia due to brain injury.
  • a speech pattern may include a frequency of neologisms and/or word approximations, or glossomania. Higher than average frequencies of neologisms and/or word approximations, or glossomania, have been associated with disorders such as schizophrenia, schizoaffective disorder, or mania.
  • a speech pattern may include a frequency of word production. A frequency of word production lower than the norm may be indicative of a brain disorder such as schizophrenia.
  • An excessive speed during speech, as in pressured speech, may be indicative of a brain disorder such as the mania of bipolar disorder, while reduced speed may be indicative of depression or a depressive episode.
  • a pattern may include a type:token ratio (i.e., number of different words (types) in relation to the total number of words spoken (tokens)).
  • a type:token ratio that is generally lower than the norm can be indicative of schizophrenia.
  • a speech pattern may include a frequency of specific words. Quantitative word counts have been used as a tool in the identification and examination of abnormal psychological processes including major depression, paranoia, and somatization disorder. A high frequency of negative emotion words or death-related words may be indicative of depression.
  • Psychologically relevant words can include those listed in one or more dictionaries of the Linguistic Inquiry and Word Count (LIWC) program (see Tausczik and Pennebaker, "The Psychological Meaning of Words: LIWC and
  • Words interpreted as carrying normative emotional qualities are found in dictionaries of two programs, Affective Norms for English Words (ANEW) and Dictionary of Affect in Language (DAL)(see Whissell C, "A comparison of two lists providing emotional norms for English words (ANEW and the DAL),” Psychol Rep., 102(2):597-600, 2008, which is incorporated herein by reference).
  • a speech pattern includes a linguistic pattern determined at the sentential level or discourse level.
  • a speech pattern can include a consistent grammatical style.
  • a pattern comprising a style that is grammatically deviant from the norm might include the overuse of the past tense, indicating detachment from the subject being discussed.
  • a pattern comprising a style that is grammatically deviant from the norm e.g., as reflected by a higher percentage of simple sentences and, in compound sentences, fewer dependent clauses may be indicative of schizophrenia.
  • a speech pattern may include a ratio of syntactic complexity (number of clauses and proportion of relative :total clauses). An abnormal ratio may indicate a brain disorder.
  • a speech pattern may include a frequency of subordinate clauses.
  • An increase in subordinate clauses has been observed in the speech of psychopaths (see, e.g., Hancock et al, "Hungry like the wolf: A word-pattern analysis of the language of psychopaths," Legal and Criminological Psychology, 2011; DOI: 10.1111/j.2044-8333.2011.02025.x, which is incorporated herein by reference).
  • a speech pattern may include a relatedness of lexical content such as semantic or sentential priming.
  • a speech pattern of abnormal priming may indicate a brain disorder such as schizophrenia.
  • a speech pattern may include a frequency of one or more use of cohesive ties, e.g., as demonstrated by references, conjunctions, or lexical cohesion.
  • a low frequency of reference ties has been observed in patients suffering from schizophrenia.
  • a speech pattern may include an hierarchical structure within a discourse, e.g., a systematic structure in which propositions branch out from a central proposition.
  • a speech pattern lacking a systematic structure may be indicative of schizophrenia.
  • a speech pattern including a linguistic pattern determined at the sentential level or discourse level may include a representation of content of thought (what the patient is talking about).
  • a speech pattern may include a representation of form of thought (the way ideas, sentences, and words are put together).
  • a speech pattern containing representations of content or form of thought that differ from those expected may indicate a psychological disorder such as schizophrenia. Examples of representations of content or form of thought observed in schizophrenia include derailment, loss of goal, perseveration, and
  • a speech pattern may include aspects of linguistic pragmatics (e.g., cohesion or coherence).
  • Abnormal patterns in pragmatics may be indicative of a brain disorder such as schizophrenia or mania. Examples of speech patterns and content of thought are discussed by Covington, et ah, idem, and by Kuperberg and Caplan idem.
  • a program for classifying parts of speech e.g., noun, verb, adjective, etc.
  • Wmatrix interface http://ucrel.lancs.ac.uk/wmatrix/
  • has been used to analyze the speech of psychopaths see Hancock, idem).
  • a speech pattern includes an acoustic quality.
  • a speech pattern includes volume.
  • excessive or reduced volume may be indicative of a symptom of a brain disorder.
  • a speech pattern includes prosody (the rhythm, stress, and intonation of speech).
  • aprosody or flattened intonation can be indicative of schizophrenia.
  • a speech pattern includes a voice quality of phonation.
  • a speech pattern includes pitch or timbre. For example, abnormalities in pitch have been observed in schizophrenics. For example, a strained quality, choking voice, or creaking voice (laryngealisation) may be indicative of a psychological disorder. Voice qualities and volume in linguistics are discussed by
  • the at least one speech pattern 142 may be represented in speech data 124 in numerical or categorical form.
  • a speech pattern represented in numerical form may include one or more numerical values representing one or more speech parameters.
  • Particular speech parameters represented in a speech pattern may be selected for the purpose of evaluating/monitoring particular brain-related disorders.
  • a speech pattern for evaluating/monitoring depression includes values representing the following parameters: speech volume, frequency of word production, frequency of pauses, and frequency of negative value words.
  • a speech pattern for evaluating/monitoring schizophrenia includes values representing frequency of word production, frequency of pauses, frequency of
  • a speech parameter or pattern may be represented in speech data 124 in categorical form; for example, frequency of word production may be categorized as low, medium, or high rather than represented by a specific numerical value.
  • signal processing circuitry 122 includes comparator 210 for comparing at least one speech pattern 142 of patient 102 with at least one characteristic speech pattern 212 to determine whether the patient has complied with the prescribed treatment regimen.
  • comparator 210 is configured to compare at least one speech pattern 142 of the patient with a plurality of characteristic speech patterns 212 . .. 212 n to determine whether the patient has complied with the prescribed treatment regimen. For example, in an aspect, the result of such a comparison is either "patient has complied" or "patient has not complied.”
  • signal processing circuitry 122 is configured to determine that patient 102 has failed to comply with the prescribed treatment regimen.
  • signal processing circuitry 122 is configured to determine that patient 102 has complied with prescribed treatment regimen 104. Determination of compliance may be accomplished by a thresholding, windowing, or distance computation of one or multiple parameters relative to characteristic threshold or range values for the parameter. For example, for a given parameter, a patient parameter value higher than a characteristic threshold value may indicate compliance of the patient with the prescribed treatment regimen, while a patient parameter value equal to or lower than the threshold value may indicate non-compliance. As another example, a patient parameter value that lies within a range of characteristic values for the parameter may indicate compliance, while a patient parameter value outside the range of characteristic values indicates non-compliance.
  • Comparator 210 may utilize various types of distance computations to determine whether patient parameter values are within a threshold distance or distance range from
  • signal processing circuitry 122 is configured to determine whether the patient has complied with the prescribed treatment regimen based upon a determination of whether the speech corresponds to at least one of a plurality of characteristic speech patterns.
  • the plurality of characteristic speech patterns can include multiple characteristic speech patterns, each corresponding to a patient speech pattern obtained at a different treatment regimen, for example different doses of a drug.
  • the drug dose taken by the patient can be determined.
  • the patient may have taken the drug, but at a lesser dose or less often than was prescribed. Accordingly, the patient's speech pattern matches the characteristic speech pattern associated with the lesser dose of drug, indicating partial, but not full, compliance of the patient with the prescribed treatment regimen.
  • speech processor 202 is configured to process at least one audio signal 116 to determine at least one speech parameter 214 indicative of whether the patient has complied with the prescribed treatment regimen.
  • Speech parameters include, but are not limited to, measures of prosody, rhythm, stress, intonation, variance, intensity/volume, pitch, length of phonemic syllabic segments, and length of rising segments, for example.
  • speech data 124 includes at least one speech parameter 214, which may include, for example, one or more of prosody, rhythm, stress, intonation, variance, intensity/volume, pitch, length of phonemic syllabic segments, and length of rising segments.
  • signal processing circuitry 122 includes comparator 210 for comparing at least one speech parameter 214 of the patient with at least one characteristic speech parameter 216 to determine whether the patient has complied with the prescribed treatment regimen.
  • comparator 210 is configured to compare at least one speech parameter 214 of the patient with a plurality of characteristic speech parameters 216i ... 216 n to determine whether the patient has complied with the prescribed treatment regimen. For example, in an aspect, the result of such a comparison is either "patient has complied" or "patient has not complied.”
  • comparator 210 is configured to compare at least one speech parameter 214 of the patient with a plurality of characteristic speech parameters 216i ...
  • a level of compliance of the patient with the prescribed treatment regimen Determination of compliance, non-compliance, or level of compliance may be performed with comparator 210 using thresholding, windowing, or distance measurements, for example, as described herein above. Similarly, determination of compliance or non-compliance of patient 102 with a prescribed treatment regimen maybe be accomplished with the use of comparator 210 for various types of speech data by comparing patient speech data 136 with one or more characteristic speech data set 218i ... 218 n , using approaches as described herein above.
  • signal processing circuitry 122 separates patient speech data 136 originating from patient 102 from speech originating from other individuals and/or from other sounds present in audio signal 116.
  • signal processing circuitry 122 includes patient identification circuitry 150, which is configured to determine the presence of the patient from at least one identity signal 152 sensed at patient location 108.
  • Signal processing circuitry 122 is configured to detect spontaneous speech 120 from patient 102 based at least in part on the determination of the presence of the patient by the patient identification circuitry 150, as indicated by presence signal 154.
  • Identifying speech 120 originating from patient 102 may be of significance, for example, if more than one individual is present, or expected to be present, at patient location 108, such that audio signal 116 may contain speech from individuals other than, or in addition to, patient 102.
  • determining the identity and/or presence of patient 102 may aid in distinguishing speech from patient 102 from speech from other people or non-speech sounds from any other sources, and may assure that conclusions based on analysis patient speech data are reflective of the compliance of patient 102 with the prescribed treatment regimen.
  • identity signal 152 can provide information regarding the presence and identity of patient 102.
  • identity signal 152 includes at least a portion of audio signal 116, wherein patient identification circuitry 150 is configured to analyze audio signal 116 to determine the presence of patient 102 by identifying at least a portion of audio signal 116 that resembles known speech of the patient (e.g., with speech pattern matching module 156), and wherein signal processing circuitry 122 is configured to detect spontaneous speech from patient 102 by identifying speech data 124
  • patient identification circuitry 150 is configured to analyze speech data signal 128 to determine the presence of the patient based on frequency analysis of the speech data signal. Magnitude or phase spectral analysis may be used, as described in McCowan, I. ; Dean, D. ; McLaren, M. ; Vogt, R. ; and Sridharan, S.; "The Delta-Phase Spectrum With Application to Voice Activity Detection and Speaker Recognition," IEEE
  • identity signal 152 includes an image signal received from an imaging device 160 at patient location 108, wherein the patient identification circuitry 150 is configured to analyze the image signal to determine the presence of the patient and to generate presence signal 154, and wherein signal processing circuitry 122 is configured to detect spontaneous speech from the patient by identifying speech data corresponding to presence of the patient detected from the image signal, as indicated by presence signal
  • Imaging device 160 may include a camera 162 or other type of imaging device known to those of skill in the art.
  • the patient identification circuitry 150 is configured to analyze the image signal to determine the presence of the patient through facial recognition, with facial recognition module 162, e.g., using approaches as described in Wheeler, Frederick W.; Weiss, R.L.; and Tu, Peter FL, "Face recognition at a distance system for surveillance applications," Fourth IEEE
  • patient identification circuitry 150 is configured to analyze the image signal to determine the presence of the patient through gait analysis, with gait analysis module 164. Identification of the patient based on gait analysis can be performed for example by methods as described in U.S. Patent 7,330,566, issued February 12, 2008 to Cutler, and Gaba, I.
  • identity signal 152 includes a biometric signal from at least one biometric sensor 166 at patient location 108, wherein the patient identification circuitry 150 is configured analyze the biometric signal to determine the presence of patient 102, and wherein signal processing circuitry 122 is configured to detect spontaneous speech from the patient by identifying speech data corresponding to presence of the patient as determined from the biometric signal, with biometric signal analysis module 168.
  • Biometric identification can include face and gait recognition, as described elsewhere herein, and recognition based on a variety of other physiological or behavioral
  • U.S. Patent 8,229,178 issued July 24, 2012 to Zhang et al which is incorporated herein by reference, describes a method for acquiring a palm vein image with visible and infrared light and extracting features from the image for authentication of individual identity.
  • Biometric identification can be based on imaging of the retina or iris, as described in U.S. Patent No. 5,572,596 issued to Wildes et al. on Nov. 5, 1996 and U.S. Patent No.
  • identity signal 152 includes at least one authentication factor, for example, a security token, a password, a digital signature, or a cryptographic key, entered by patient 102 via user input device 260.
  • User input device 260 can include various types of user input devices or controls as are well known to those of ordinary skill in the art, including but not limited to keyboards, touchpads, touchscreen, mouse, joystick, microphone or other voice input, buttons, or switches.
  • One or more user input device 260 in local system 106 can be used to receive various types of user inputs relating to operation of local system 106, not limited to entry of an authentication factor.
  • identity signal 152 includes a device identification code 262, which identifies a device or component of local system 106.
  • Device identification code 262 may be, for example, a cell phone identification code, such as an electronic serial number, a mobile identification number, or a system identification code. In various aspects, device identification code 262 identifies a cell phone 180, a computing system 182, or a stand-alone microprocessor-based device 186, or a component thereof. Device identification code 262 can serve to identify patient 102 providing the identified device, for example a personal computer or cell phone, is consistently used only by patient 102.
  • a cell phone identification code such as an electronic serial number, a mobile identification number, or a system identification code.
  • device identification code 262 identifies a cell phone 180, a computing system 182, or a stand-alone microprocessor-based device 186, or a component thereof.
  • Device identification code 262 can serve to identify patient 102 providing the identified device, for example a personal computer or cell phone, is consistently used only by patient 102.
  • identity signal 152 includes a radio frequency identification (RFID) signal, e.g., from an RFID device 170, which may be carried, worn by, or otherwise associated with patient 102 and sensed by RFID sensor 282.
  • RFID device 170 can be a passive RFID in a tag or chip associated with the patient, and RFID sensor 282 can be a sensed with an active RFID reader may be used.
  • presence signal 154 is provided as an input to signal processing circuitry 122. Presence of patient 102 may be indicated by a value of presence signal 154.
  • presence signal 154 is a binary signal; e.g., presence signal 154 has a high value if the patient is present or a low value if the patient is not present (or vice versa).
  • patient speech data 124 is acquired from audio signal 116 only when the value of presence signal 154 indicates that patient 102 is present.
  • presence signal 154 is a continuous valued signal that indicates the probability that the patient is present.
  • presence signal 154 has a value of 100 if there is 100 percent probability that the patient is present, a value of zero if there is zero percent probability that the patient is present, or an intermediate value if there is an intermediate probability that the patient is present. It will be appreciated that in some contexts, the determination of whether the patient is present or absent will be relatively straightforward, in which case a binary presence signal may be appropriate, whereas in others (e.g., in cases where the presence of the patient must be distinguished from the presence of other individuals) there is some likelihood of error in identifying the presence of the patient (with the likelihood of error potentially dependent upon the number and identity of the other individuals present), such that an indication of the probability that the patient is present may be more appropriate.
  • FIG. 3 provides greater detail regarding monitoring system 110 at monitoring location 112.
  • speech identification circuitry 140 in monitoring system 110 includes patient identification circuitry 300 configured to determine a presence of the patient from at least one identity signal 302 received at monitoring location 112 from the patient location, wherein speech identification circuitry 140 is configured to identify patient speech data 136 corresponding to speech from the patient in the speech data 124 based at least in part on the determination of the presence of the patient by patient identification circuitry 300.
  • Presence of the patient is indicated by a value of presence signal 304.
  • presence signal 304 is a binary signal; e.g., presence signal 304 has a high value if the patient is present or a low value if patient is not present (or vice versa).
  • presence signal 304 is a continuous valued signal that indicates the probability that the patient is present. For example, presence signal 304 has a value of 100 if there is 100 percent probability that the patient is present, a value of zero if there is zero percent probability that the patient is present, or an intermediate value if there is an intermediate probability that the patient is present.
  • the determination of whether the patient is present or absent will be relatively straightforward, and a binary presence signal may be appropriate, whereas in others (e.g., in cases where the presence of the patient must be distinguished from the presence of other individuals) there is some likelihood of error in identifying the presence of the patient (with the likelihood of error potentially dependent upon the number and identity of the other individuals present), such that an indication of the probability that the patient is present may be more appropriate.
  • identity signal 302 includes at least a portion of speech data signal 128, and patient identification circuitry 300 is configured to analyze speech data signal 128 to determine the presence of the patient based on speech data signal 128, by identifying at least a portion of speech data signal 128 that resembles a known speech data signal of the patient, with speech comparator 306. Accordingly, speech identification circuitry 140 is configured to identify patient speech data 136 by identifying speech data 124 corresponding to presence of the patient detected from the speech data signal 128. For example, a continuous speech system may be used for identifying the speaker, as described in Chandra, E. and Sunitha, C, "A review on Speech and Speaker
  • patient identification circuitry 300 is configured to analyze speech data signal 128 to determine the presence of the patient based on frequency analysis of the speech data signal, with frequency analyzer 308. Magnitude or phase spectral analysis may be used, as described in McCowan, I. ; Dean, D. ; McLaren, M. ; Vogt, R.
  • identity signal 302 includes an image signal received from an imaging device at the patient location (e.g., imaging device 160 as shown in FIG. 2), wherein patient identification circuitry 300 is configured to analyze the image signal to determine the presence of the patient, and wherein speech identification circuitry 140 is configured to identify patient speech data 136 by identifying speech data 124 corresponding to presence of the patient detected from the image signal.
  • patient identification circuitry 300 is configured to analyze the image signal to determine the presence of the patient
  • speech identification circuitry 140 is configured to identify patient speech data 136 by identifying speech data 124 corresponding to presence of the patient detected from the image signal.
  • patient identification circuitry 300 may be configured to analyze the image signal to determine the presence of the patient through facial recognition, with facial recognition circuitry 310, for example using approaches as described in Wheeler, Frederick W.; Weiss, R.L.; and Tu, Peter FL, "Face recognition at a distance system for surveillance applications," Fourth IEEE International Conference on Biometrics: Theory Applications and Systems (BTAS), 2010 Page(s): 1 - 8 (DOI: 10.1109/BTAS.2010.5634523), and Moi Hoon Yap; Ugail, H.; Zwiggelaar, R.; Rajoub, B.; Doherty, V.; Appleyard, S.; and Hurdy, G., "A Short Review of Methods for Face Detection and Multifractal Analysis, " International Conference on CyberWorlds, 2009.
  • patient identification circuitry 300 may be configured to analyze the image signal to determine the presence of the patient through gait analysis, with gait analysis circuitry 312. Identification of the patient based on gait analysis can be performed, for example by methods as described in U.S. Patent 7,330,566, issued February 12, 2008 to Cutler, and Gaba, I. and Kaur P., "Biometric Identification on The Basis of BPNN Classifier with Other Novel Techniques Used For Gait Analysis," Intl. J. of Recent Technology and Engineering (IJRTE) ISSN: 2277-3878, Vol. 2, issue 4, Sept 2013, pp. 137 - 142, both of which are incorporated herein by reference.
  • the identity signal includes a biometric signal from at least one biometric sensor 166 at the patient location 108 (as shown in FIG. 2), wherein patient identification circuitry 300 in FIG. 3 is configured to analyze the biometric signal to determine the presence of the patient, with the use of biometric analysis circuitry 314, and wherein speech identification circuitry 140 is configured to identify patient speech data 136 by identifying speech data 124 corresponding to presence of the patient detected from the biometric signal. Biometric signal analysis can be performed as described elsewhere herein.
  • identity signal 302 includes at least one authentication factor, which may be, for example, a security token, a password, a digital signature, or a cryptographic key.
  • an authentication factor is entered by the patient via a user input device, e.g., user input device 260 in FIG. 2.
  • User input device 260 can include various types of user input devices or controls as are well known to those of ordinary skill in the art, including but not limited to a keyboard, touchpad, touchscreen, mouse, joystick, or microphone or other voice input.
  • patient identification circuitry 300 includes authentication circuitry 316 for determining the identity of the patient based upon the authentication factor.
  • identity signal 302 includes a cell phone identification code, which may be, for example, an electronic serial number, a mobile identification number, or a system identification code, and patient identification circuitry 300 include cell phone
  • identification circuitry 318 Combinations of several types of identity signals can also be used (e.g., speech and video, as described in Aleksic, P.S. and Katsaggelos, A.K. "Audio- Visual Biometrics," Proceedings of the IEEE Volume: 94 , Issue: 11, Page(s): 2025 - 2044, 2006 (DOI: 10.1109/JPROC.2006.886017 ), which is incorporated herein by reference).
  • identity signals e.g., speech and video, as described in Aleksic, P.S. and Katsaggelos, A.K. "Audio- Visual Biometrics," Proceedings of the IEEE Volume: 94 , Issue: 11, Page(s): 2025 - 2044, 2006 (DOI: 10.1109/JPROC.2006.886017 ), which is incorporated herein by reference).
  • identity signal 302 may conveniently be a cell phone identification code when local system 106 is embodied as a cell phone configured with application software, as indicated at 180 in FIG. 2.
  • patient identification circuitry 300 includes cell phone identification circuitry 318.
  • identity signal 302 includes an RFID signal, e.g., from RFID device 170 associated with patient 102 at patient location 108, as depicted and described in connection with FIG. 2, and patient identification circuitry 300 includes RFID circuitry 320.
  • monitoring system 110 includes input device 330 for receiving prescription information 332 indicative of the treatment regimen prescribed to the patient.
  • Input device 330 may be a user input device 334 (e.g., a keyboard, touchpad, touchscreen, mouse, joystick, microphone or other voice input, etc.) adapted for receiving prescription information from, e.g., medical care provider 151, or data input device 336 adapted to receive data from another device (e.g., a computer system, a networked system, a cell phone, a barcode reader, a flash drive, a disk drive, etc. via a wired or wireless connection as is well known in the relevant arts).
  • a user input device 334 e.g., a keyboard, touchpad, touchscreen, mouse, joystick, microphone or other voice input, etc.
  • data input device 336 adapted to receive data from another device (e.g., a computer system, a networked system, a cell phone, a barcode reader, a flash drive, a disk drive, etc
  • monitoring system 110 includes at least one data storage device 340 for storing prescription information indicative of the treatment regimen prescribed to the patient.
  • Data stored in data storage device 340 may include, but is not limited to speech data 124, prescription information 332 (including details of the prescribed treatment regimen), stored messages regarding device status, device settings, instructions, or conclusions, for example.
  • Data storage device 340 is a data storage device or system that forms a part of monitoring system 110, or is accessible by monitoring system 110, e.g., on a server and/or cloud-based data storage system.
  • data storage device 340 includes one or more database containing electronic medical records, for example.
  • the at least one receiving device 130 which receives speech data signal 128 transmitted to monitoring location 112 from patient location 108, includes a wireless receiver 350, a computer network connection 352, a USB port 354, or a computer drive 356.
  • Transmission of data or information to receiving device 130 thus encompasses wireless or wired transmission, and also device-based transmission involving transfer of a data from local system 106 at patient location 108, via a data storage device (e.g., a flash drive or DVD), to a data reading device (USB port 354 or computer drive 356) in monitoring system 110 that reads data from the data storage device.
  • Monitoring system 110 in some aspects includes more than one receiving device, and multiple receiving devices may be of the same or different types.
  • receiving device 130 receives various types of data and/or information from local system 106 at patient location 108, not limited to speech data signal 128. Furthermore, in some aspects receiving device 130 receives data or information from devices and systems other than local system 106. For example, in some aspects, receiving device 130 may also serve as data input device 336.
  • At least one of speech identification circuitry 140 and compliance determination circuitry 144 includes a speech processor, (see, e.g., speech processor 360 in speech identification circuitry 140 and speech processor 362 in compliance determination circuitry 144.)
  • a single speech processor may be shared by speech identification and compliance determination circuitry.
  • compliance determination circuitry 144 includes speech processor 362 for analyzing the patient speech data 136 to determine the at least one patient speech pattern 142 and a comparator 366 for comparing the at least one patient speech pattern 142 with one or multiple characteristic speech patterns 368i - 368 n .
  • One or more characteristic speech patterns 368i - 368 n may be stored in data storage device 340.
  • operation of comparator 366 may be substantially similar to that of comparator 210;
  • system 100 includes either comparator 210 in local system 106 or comparator 366 in monitoring system 110, but not both.
  • system 100 includes some degree of redundancy, such that local system 106 includes comparator 210 and monitoring system 110 includes comparator 366.
  • speech data transmitted in speech data signal 128 may be minimally processed.
  • speech data signal 128 may contain processed speech data (e.g., speech patterns and/or parameters). However, even if speech processing is performed in local system 106, both processed and
  • unprocessed speech data e.g., raw speech data as well as speech parameters and or speech patterns
  • speech data signal 128 may be included in speech data signal 128.
  • patient speech data 136 may be compared directly with characteristic speech data sets, rather than being processed first by speech processor 362 to determine patient speech pattern 142, such that the comparison is performed between patient speech pattern 142 and characteristic speech patterns 368i - 368 n , as described above.
  • comparator 366 in compliance determination circuitry 144 compares patient speech data 136 with one or multiple characteristic speech data sets 370 1 - 370 n indicative of the characteristic speech pattern, where each said characteristic speech data set is indicative of a characteristic speech pattern.
  • the result of the comparison performed by comparator 366 is a determination that the patient speech data (or patient speech pattern derived therefrom) either does, or does not, match one or more characteristic speech data sets or speech patterns. As discussed above, if there is a match, conclusion 149 is generated regarding whether the patient has complied with the prescribed treatment regimen.
  • the comparison performed by comparator 366 (which may include thresholding, windowing, distance computation, for example, as discussed herein above) will result in production of a signal by compliance determination circuitry that indicates at least whether the patient has complied with the prescribed treatment regimen, and alternatively, or in addition, a level of compliance with the prescribed treatment regimen.
  • the compliance determination circuitry 144 is configured to determine that the patient has failed to comply with the prescribed treatment regimen.
  • medical care provider 151 or another party concerned with the patient's health and well- being, such as a parent, family member, caretaker, healthcare provider
  • Notification can be provided by reporting conclusion 149 with reporting circuitry 148.
  • compliance determination circuitry 144 is configured to determine that the patient has complied with the prescribed treatment regimen, e.g. by generating determination 145.
  • monitoring system 110 reports conclusion 149 with reporting circuitry 148 when the patient is in compliance with the prescribed treatment regimen, as indicated by determination 145.
  • compliance determination circuitry can be configured to determine both compliance and non-compliance, and additionally, or alternatively, level of compliance (either at specific levels or simply partial compliance), as indicated by a value of determination 145.
  • Compliance or lack thereof can be represented by appropriate text or numerical value in a displayed report or email e.g., reported by reporting circuitry 148, or represented by a binary value in data stored by data storage circuitry 382.
  • level of compliance can be represented by a continuous value (e.g., percent compliance) or a text descriptor selected from a number of text descriptors corresponding to different levels of compliance (e.g., non-compliance, low compliance, intermediate compliance, near- full compliance, full compliance).
  • Reporting circuitry 148 provides for formatting determination 145 appropriately (e.g., by including appropriate messages to accompany the value of the determination) and for deciding whether and how to report the conclusion, based upon user preferences. For example, who is notified (medical care provider versus family member) or how notification is provided (stored in an event record, via email, or via a text message to a cell phone) may depend on the patient's level of compliance and the specifics of the patient. That is reporting circuitry 148 can generate different levels of notifications depending on how serious a problem non-compliance is likely to be for the patient.
  • reporting circuitry 148 is used to report a conclusion 149 to medical care provider 151 or another party.
  • reporting circuitry 148 includes display device 372.
  • Reporting circuitry 148 may include circuitry for generating a notification. For example, a notification may be displayed on display device 372.
  • Generating a notification may include retrieving a stored notification 374 from data storage device 340, e.g., selected from among one or more notifications stored in data storage device 340, as discussed above in connection with notification circuitry 250 in local system 106.
  • Notifications may take the form of text or numerical codes, for example.
  • reporting circuitry 148 includes circuitry (e.g., wireless transmitter 378) for transmitting a notification to a wireless device 376.
  • Wireless device 376 may be, for example, a pager, cell phone, or other wireless device used by a medical care provider or family member interested in tracking the status of the patient.
  • reporting circuitry 148 includes audio alarm circuitry 380 for generating an audio alarm, e.g., a tone or voice alert be delivered via a speaker, or activating a bell, buzzer, beeper, or the like to inform medical care provider 151 of the status of the patient.
  • an audio alarm e.g., a tone or voice alert be delivered via a speaker, or activating a bell, buzzer, beeper, or the like to inform medical care provider 151 of the status of the patient.
  • reporting circuitry 148 includes data storage circuitry 382 for storing a notification in a data storage device, e.g., in event history 390.
  • data storage circuitry 382 may provide for storage of a notification in event history 390 in conjunction with information regarding the time at which the notification was generated, obtained, for example from timing circuitry 386.
  • timing circuitry 386 includes a clock 388 and/or timer 396.
  • Event history 390 may be a part of the subject's electronic medical records, and may be stored locally in monitoring system 110, or elsewhere.
  • FIGS. 1 - 3 Systems and system components as illustrated generally in FIGS. 1 - 3 may be better understood by reference to the examples shown in FIG. 4 - 7.
  • FIG. 4 depicts an embodiment of a system 400 for monitoring compliance of a patient 402 with a prescribed treatment regimen, implemented in connection with the patient's personal computer 410.
  • system 400 is used for monitoring compliance of patient 402 while patient 402 participates in a video consultation with medical care provider 408.
  • system 400 can in addition (or alternatively) be used to monitor compliance of patient 402 during routing activities with data streaming device 428, which is powered by a USB port of computer 410.
  • System 400 includes system 404 at a patient location and monitoring system 406 used at a monitoring location by a medical care provider 408.
  • System 404 includes a personal computer system including computer 410, microphone 412 for detecting patient speech 414, display 416, camera 418 (which is shown here as being built into display 416, but could also be packaged separately), and keyboard 420.
  • patient 402 participates in a video consultation with medical care provider 408, with patient voice data being captured by microphone 412, patient image data being captured by camera 418, and both voice and image data being transmitted to computer 430 of monitoring system 406 via network 422.
  • An image 432 of patient 402 is displayed on display 434 for viewing by medical care provider 408.
  • Camera 436 captures an image 424 of medical care provider 408, which is transmitted to system 404 via network 422, where it is displayed on display 416.
  • Microphone 438 captures voice data from medical care provider 408, which is also sent to system 404 and may be delivered to patient 402 via speakers 426. Similar, patient voice data can be presented to medical care provider 408 via speakers 446.
  • a report 448 containing a conclusion regarding compliance of patient 402 with a prescribed treatment regimen is displayed on display 434.
  • report 448 includes a listing of a patient ID number, a date, a time, and a statement regarding patient compliance, e.g., "Patient speech parameters indicate partial compliance with prescribed treatment regimen.”
  • Patient identity is determined by entry of an authentication factor (e.g., login and password) by patient 402 when logging in for video conference.
  • data streaming device 428 captures speech from patient 402 with a built-in microphone and provides for transmission of speech data to network 422. Patient identity is determined by voice recognition. Patient speech data is transmitted from data streaming device 428 to monitoring system 406 via network 422, for processing and reporting to medical care provider 408.
  • FIG. 5 depicts a system 500 for monitoring compliance of a patient 502 with a prescribed treatment regimen that includes a stand-alone
  • stand-alone device 504 is configured for easy operation, with minimal user controls.
  • Stand-alone device 504 includes dedicated hardware, firmware and/or software designed to perform the functions described herein.
  • Device 504 is a stand-alone microprocessor-based device in that computing capability at patient location 506 is provided by a dedicated special purpose device and the system does not utilize the computing capability of, e.g., a personal computer or cell phone at the patient location; however, stand-alone device 504 may operate in combination with other system components at the patient location as well as at monitoring location 508.
  • Stand-alone device 504 includes a microphone 510 for sensing patient speech, as well as background sounds. In the example of FIG.
  • patient 502 suffers from depression in which the patient is less active and/or talkative than usual during an episode of the disorder.
  • the content of the patient's speech may also change before or during an episode. Both quantity and content of patient speech may be indicative of the patient's mental state, and hence of the patient's compliance with a prescribed treatment regimen. If patient 502 is present, and microphone 510 detects an audio signal that contains little or no speech or sounds of physical activity of the patient at a time of day when speech or activity would be expected, device 504 generates a report indicating non-compliance of patient 502 with the prescribed treatment regimen.
  • Presence of the patient in the vicinity of device 504, as well as the identity of the patient, can be detected by sensing the presence of an RFID armband 512 worn by patient 502 with an RFID sensor in device 504.
  • Device 504 includes a clock/timing device for tracking the time of day. If non-compliance of the patient with the prescribed treatment regimen is detected, device 504 sends information to computing system 514 at monitoring location 508, via network 516.
  • Computing system 514 includes computer 518, display 520, and keyboard 522.
  • Computer 518 presents information 524, including report 526 concerning patient 502 on display 520, for viewing by medical care provider 528.
  • FIG. 6 depicts an example of a system 600 for monitoring patient compliance that is suitable for monitoring a patient 602 in a group setting, for example a group home.
  • System 600 includes a local system 604 in patient location 606, and monitoring system 608 in monitoring location 610.
  • Local system 604 includes imaging device 612, which in this example is a video camera, and microphone 614 connected to circuitry 616.
  • Circuitry 616 transmits a speech data signal 618 containing a speech signal from microphone 614 and identity signal 620 containing a video signal from imaging device 612 to network 622 and from there to monitoring system 608.
  • Circuitry 616 includes conventional closed- circuit TV circuitry that processes speech 636 (e.g., by amplification and filtering) before transmitting it to monitoring system 608.
  • Monitoring system 608 includes computer 624 connected to display 626 by data link 628. Monitoring system 608 can be located in a separate room of a group home from local system 604, connected to local system 604 by a LAN or WAN, for example. Video data contained in identity signal 620 is used to generate image 630, which is displayed on display 626, along with report 632, for viewing by medical care provider 634 (or alternatively, a counselor, or group home staff member, for example). Report 632 is generated by software running on computer 624 based on analysis of speech data signal 618. Speech 636 from patient 602 is separated from speech 638 from second patient 640 based on analysis of identity signal 618.
  • analysis of identity signal 618 includes one or both of facial recognition or gait analysis, using methods as discussed herein above.
  • Speech 636 from patient 602 is analyzed to determine whether patient 602 has complied with the prescribed treatment regimen.
  • patient 602 exhibits an agitated physical activity pattern (detectable in image 630) and agitated speech pattern (detectable in speech 636), indicating that patient 602 has failed to comply with a prescribed treatment regimen.
  • report 632 states "ALERT: Patient 602 speech indicates non-compliance with prescribed treatment regimen.”
  • an audio alarm (a beep or buzzing sound) is generated on speaker 644 to attract the attention of medical care provider 634.
  • Medical care provider 634 observes the behavior of patient 602 on display 626 in addition to listening to the accompanying audio signal presented on speaker 644.
  • compliance of patient 640 with a prescribed treatment regimen is also monitored: speech of patient 640 can be detected, separated from the speech of patient 602, analyzed, and compliance reported in the same manner.
  • report 642 indicates the status of patient 640: "STATUS: Patient 640 speech indicates compliance.”
  • FIG. 7 depicts an example of a system 700 for monitoring compliance of a patient
  • System 700 includes cell phone 704, which is a cell phone used by patient 702, configured with application software 706, and cell phone 708, configured with application software 710, and used by medical care provider 712.
  • System 700 is used to monitor compliance of patient 702 with a prescribed treatment regimen by analyzing speech 714 of patient 702 during the course of routine use of cell phone 704 by patient 702, for example to communicate with person 716 (e.g., a friend) using a cell phone 718.
  • person 716 e.g., a friend
  • communication signal 720 containing voice data from patient 702 is transmitted to cellular network 722 and from there to cell phone 718.
  • cellular communication signal 724 containing voice data from person 716 is transmitted from cell phone 718 to cell phone 704 via cellular network 722.
  • a second cellular signal 726 is transmitted via cellular network 722 to cell phone 708.
  • Second cellular signal 726 contains speech data signal 730 and identity signal 732, which are processed by application software 710 on cell phone 708 to generate report 734.
  • speech data signal 730 contains speech parameters that characterize the speech of patient 702, but not the speech itself, therefore maintaining privacy of patient 702 's communications.
  • speech data signal 730 does not contain speech from person 716.
  • speech data signal 730 occurs on cell phone 704, through the use of application software 706, to perform signal processing functions as described elsewhere herein.
  • report 734 is presented to medical care provider 712 in the form of a text message displayed on screen 736 of cell phone 708.
  • FIG. 8 illustrates a generalized form of circuitry-based systems as depicted in FIGS. 1 - 7. Although specific embodiments are described herein, those skilled in the art will appreciate that methods and systems as described herein can be implemented in various ways. Reference is made herein to various circuitry subsystems (e.g., signal processing circuitry 122, compliance determination circuitry 144, and speech
  • local system 105 includes control circuitry for controlling at least one of the at least one audio sensor 114, the signal processing circuitry 122, and the at least one transmitting device 126.
  • Control circuitry of local system 105 in various aspects control other system components and functions, e.g., communication circuitry 284, speech processor 202, notification circuitry 250, as well as data storage, communication, and input/output functions.
  • monitoring system 110 includes control circuitry for controlling at least one of the at least one receiving device 130, the speech identification circuitry 140, the compliance determination circuitry 144, and the reporting circuitry 148, and other system components.
  • control/processing circuitry 802 includes any or all of digital and/or analog components 804, one or more processor 806 (e.g., a
  • System 800 may include other components as known to those skilled in the art, e.g., one or more power supply 822, and I/O structure 824.
  • I/O structure 824 permits communication with various types of user interface devices (represented by user interface 830) and various types of remote device 832, which may have control/ processing capability conferred by control/ processing circuitry 834.
  • circuitry having at least one discrete electrical circuit, electrical circuitry having at least one integrated circuit, electrical circuitry having at least one application specific integrated circuit, electrical circuitry forming a general purpose computing device configured by a computer program (e.g., a general purpose computer configured by a computer program which at least partially carries out processes and/or devices described herein, or a microprocessor configured by a computer program which at least partially carries out processes and/or devices described herein), electrical circuitry forming a memory device, which may include various types of memory (e.g., random access, flash, read only, etc.), electrical circuitry forming a communications device (e.g., transmitting device 126 and receiving device 130) (e.g., a modem, communications switch, optical-electrical equipment, etc.), and/or any non-electrical analog thereto, such as optical or other analogs (e.g., graphene based circuitry).
  • a communications device e.g., transmitting device 126 and receiving device 130
  • a data processing system generally includes one or more of a system unit housing, a video display, memory such as volatile or non- volatile memory, processors such as microprocessors or digital signal processors, computational entities such as operating systems, drivers, graphical user interfaces, and applications programs, one or more interaction devices (e.g., a touch pad, a touch screen, an antenna, etc.), and/or control systems including feedback loops and control motors (e.g., feedback for sensing position and/or velocity; control motors for moving and/or adjusting components and/or quantities).
  • a data processing system may be implemented utilizing suitable commercially available components, such as those typically found in data computing/communication and/or network computing/communication systems.
  • transmitting device 126 in local system 106 and receiving device 130 in monitoring system 110 are configured to provide a communication link between the two locations.
  • transmitting device 126 and receiving device 130 provide a wireless communication link.
  • a wireless communication link may also be established between monitoring system 1 10 and wireless device 376, as shown in FIG. 3.
  • a wireless communication link includes at least one of a radio frequency, wireless network, cellular network, satellite, WiFi, BlueTooth, Wide Area Network, Local Area Network, or Body Area Network communication link.
  • Various types of communication links are suitable for providing communication between two remote locations. Communication between locations remote from each other may take place over telecommunications networks, for example public or private Wide Area Network (WAN).
  • WAN Wide Area Network
  • LAN Local Area Network
  • WiFi Wireless Fidelity
  • portions (but not the entirety) of communication networks used in remote communications may include technologies suitable for use in physically localized network, such as Ethernet or WiFi.
  • system components are considered “remote” from each other if they are not within the same room, building, or campus.
  • a remote system may include components separated by a few miles or more.
  • system components may be considered "local” to each other if they are located within the same room, building, or campus.
  • FIG. 9 is a flow diagram of a method 900 relating to monitoring of a patient at a patient location to determine compliance of the patient with a prescribed treatment regimen.
  • Method 900 includes sensing at least one audio signal including spontaneous speech from a patient with at least one audio sensor at a patient location, the patient having a brain-related disorder and a prescribed treatment regimen for treating at least one aspect of the brain-related disorder, as indicated at 902; detecting spontaneous speech of the patient in the at least one audio signal with signal processing circuitry at the patient location, as indicated at 904; generating with the signal processing circuitry speech data including data indicative of whether the patient has complied with the prescribed treatment regimen, as indicated at 906; and transmitting a speech data signal containing the speech data including data indicative of whether the patient has complied with the prescribed treatment regimen to a receiving device at a monitoring location with at least one transmitting device at the patient location, as indicated at 908.
  • Generation of a speech data signal containing speech data including data indicative of whether the patient has complied with the prescribed treatment regimen
  • FIGS. 10 - 18 depict variations and expansions of method 900 as shown in FIG. 9.
  • steps 902 - 908 are as described generally in connection with FIG. 9.
  • method steps outlined with dashed lines represent steps that are included in some, but not all method aspects, and combinations of steps other than those specifically depicted in the figures are possible as would be known by those having ordinary skill in the relevant art.
  • FIG. 10 depicts method 1000, which includes steps 902 - 908 as described above, and also includes receiving a signal indicative of initiation of treatment of the patient according to the prescribed treatment regimen and beginning to sense the at least one audio signal responsive to receipt of the signal indicative of initiation of treatment of the patient, as indicated at 1002.
  • a treatment signal 272 is transmitted to local system 106 from monitoring system 110, in response to an input indicating initiation of treatment from medical care provider 151, provided via a user input device (e.g., a keyboard or keypad), for example.
  • patient 102 may provide an input via a user input device (e.g., a keyboard or keypad) to indicate that treatment has been initiated (e.g., that the patient took a dose of medication).
  • FIG. 11 depicts a further method 1100, which includes performing substantially continuously at least one of sensing the at least one audio signal, detecting the spontaneous speech of the patient, generating the speech data, and transmitting the speech data signal, as indicated at 1102.
  • Continuous monitoring may be appropriate, for example, in situations where the patient's condition is unstable and likely to change abruptly or dramatically, such that prompt detection and correction is desirable.
  • method 1100 includes performing intermittently at least one of sensing the at least one audio signal, detecting the spontaneous speech of the patient, generating the speech data, and transmitting the speech data signal, as indicated at 1104. Intermittent sensing may be appropriate for patients whose condition is sufficiently stable that continuous monitoring is not required.
  • Intermittent sensing may be event driven (for example, sensing can be performed when the patient uses a phone for communication, or when the patient uses a personal computer).
  • method 1100 includes performing, according to a schedule, at least one of sensing the at least one audio signal, detecting the spontaneous speech of the patient, generating the speech data, and transmitting the speech data signal, as indicated at 1106.
  • Sensing can be performed according to a schedule, under control of timing circuitry 244 in local system 106, as shown in FIG. 2.
  • Timing circuitry 244 includes clock 274 and/or timer 276 and controls sensing according to stored schedule 278, for example by sending an interrupt to initiate sensing at the time or times specified by schedule 278, based on time from clock 274/timer 276.
  • timing may be controlled by timing circuitry 386 in monitoring system 110, according to schedule 398, based on time from clock 388 and/or timer 396.
  • method 1200 includes determining a presence of the patient with patient identification circuitry based on at least one identity signal sensed at the patient location, wherein detecting spontaneous speech of the patient in the at least one audio signal with the signal processing circuitry at the patient location includes detecting speech from the patient based at least in part on the determination of the presence of the patient by the patient identification circuitry, as indicated at 1202.
  • the identity signal may include, for example, the audio signal, as indicated at 1204; an image signal, as indicated at 1206; a biometric signal, as indicated at 1208; or an RFID signal, as indicated at 1210.
  • method 1200 includes beginning detecting the audio signal, as indicated at 1204; an image signal, as indicated at 1206; a biometric signal, as indicated at 1208; or an RFID signal, as indicated at 1210.
  • method 1200 includes beginning detecting the audio signal, as indicated at 1204; an image signal, as indicated at 1206; a biometric signal, as indicated at 1208; or an RFID signal, as indicated at 1210.
  • method 1200 includes beginning
  • determining the presence of the patient with the patient identification circuitry as indicated at 1212. For example, in the embodiment of FIG. 6, in an aspect, detection of spontaneous speech from patient 602 is initiated in response to determining the presence of patient 602 based on recognition of patient 602 in image 630, using one or both of gait or facial recognition techniques.
  • a method 1300 includes receiving a signal representing the prescribed treatment regimen from the monitoring location, as indicated at 1302 (e.g., prescription information signal 338 in FIGS. 2 and 3); receiving an instruction from the monitoring location, as indicated at 1304 (e.g., instruction 399 in FIGS. 2 and 3); and generating a notification with notification circuitry at the patient location, as indicated at 1306; and may also include one or more of sending the notification via email, as indicated at 1308; transmitting the notification to a wireless device, as indicated at 1310; and storing the notification in a data storage device, as indicated at 1312 (see, e.g., discussion of notification generation by notification circuitry 250 in FIG. 2).
  • transmitting the speech data signal includes transmitting a wireless signal, as indicated at 1402; transmitting a signal via the internet, as indicated at 1404; or storing the speech data on a USB device, as indicated at 1406. See, e.g., transmitting device 126, as depicted and described in connection with FIG. 2.
  • Method 1400 may include storing the at least one audio signal in a data storage device, as indicated at 1408; storing the speech data in a data storage device, as indicated at 1410 (e.g., data storage device 200 in FIG.
  • Method 1400 may include identifying at least one section of the at least one audio signal containing spontaneous speech of the patient, as indicated at 1414. Method 1400 may then also include one or both of including the at least one section of the at least one audio signal containing spontaneous speech of the patient in the speech data, as indicated at 1416, and processing the at least one audio signal to exclude at least one portion of the at least one audio signal that does not contain the spontaneous speech of the patient, as indicated at 1418.
  • FIG. 15 depicts a method 1500, which in an aspect includes transmitting the speech data signal to the receiving device at the monitoring location with the at least one transmitting device at the patient location if the speech data is indicative of the patient not complying with the prescribed treatment regimen, as indicated at 1502.
  • a method 1500 which in an aspect includes transmitting the speech data signal to the receiving device at the monitoring location with the at least one transmitting device at the patient location if the speech data is indicative of the patient not complying with the prescribed treatment regimen, as indicated at 1502.
  • method 1500 includes processing at least one section of the at least one audio signal to determine at least one speech pattern of the patient, as indicated at 1504.
  • the speech data may then include the at least one speech pattern of the patient, as indicated at 1506.
  • method 1500 may also include comparing the at least one speech pattern with at least one characteristic speech pattern to determine whether the patient has complied with the prescribed treatment regimen, as indicated at 1508.
  • method 1500 includes determining at least one speech parameter indicative of whether the patient has complied with the prescribed treatment regimen, wherein the speech data includes the at least one speech parameter, as indicated at 1510, and may then also include comparing the at least one speech parameter with at least one characteristic speech parameter to determine whether the patient has complied with the prescribed treatment regimen, as indicated at 1512.
  • the brain-related disorder is schizophrenia, as indicated at 1602; Parkinson's disease, as indicated at 1604; an Autism Spectrum Disorder, as indicated at 1606; dementia, as indicated at 1608; Bipolar Disorder, as indicated at 1610; or depression, as indicated at 1612.
  • a brain-related disorder is a mental disorder, psychological disorder, or psychiatric disorder.
  • a mental disorder, psychological disorder, or psychiatric disorder can include, for example, a psychological pathology, psychopathology, psychosocial pathology, social pathology, or psychobiology disorder.
  • a mental disorder, psychological disorder, or psychiatric disorder can be any disorder categorized in any Diagnostic and Statistical Manual (DSM) or International Statistical Classification of Diseases (ICD) Classification of Mental and Behavioural Disorders text, and may be, for example and without limitation, a neurodevelopmental disorder (e.g., autism spectrum disorder or attention-deficit/hyperactivity disorder), a psychotic disorder (e.g., schizophrenia), a mood disorder, a bipolar disorder, a depressive disorder, an anxiety disorder, an obsessive- compulsive disorder, a trauma- or stressor-related disorder, a dissociative disorder, a somatic symptom disorder, an eating disorder, an impulse-control disorder, a substance- related or addictive disorder, a personality disorder (e.g., narcissistic personality disorder or antisocial personality disorder), a neurocognitive disorder, a major or mild
  • neurocognitive disorder e.g., one due to Alzheimer's disease, traumatic brain injury, HIV infection, prion disease, Parkinson's disease, Huntington's disease, or
  • a mental disorder, psychological disorder, or psychiatric disorder can be any disorder described by the NIH National Institute of Mental Health (NIMH) Research Domain Criteria Project and may include a biological disorder involving brain circuits that implicate specific domains of cognition, emotion, or behavior.
  • a brain-related disorder includes a serious mental illness or serious emotional disturbance.
  • a brain-related disorder includes a serious mental illness or serious emotional disturbance, a mental disorder, psychological disorder, or psychiatric disorder.
  • a brain disorder is a traumatic disorder, such as a traumatic brain injury.
  • Traumatic brain injury-induced disorders may present with dysfunction in cognition, communication, behavior, depression, anxiety, personality changes, aggression, acting out, or social inappropriateness. See, e.g., Jeffrey Nicholl and W. Curt LaFrance, Jr., "Neuropsychiatric Sequelae of Traumatic Brain Injury," Semin Neurol. 2009,
  • a brain-related disorder is a lesion-related disorder.
  • a brain lesion can include, for example and without limitation, a tumor, an aneurysm, ischemic damage (e.g., from stroke), an abscess, a malformation, inflammation, or any damage due to trauma, disease, or infection.
  • An example of a lesion-related disorder is a disorder associated with a right-hemisphere lesion.
  • a brain disorder is a neurological disorder.
  • a neurological disorder may be, for example and without limitation, Alzheimer's disease, a brain tumor, a developmental disorder, epilepsy, a neurogenetic disorder, Parkinson's disease,
  • NINDS National Institutes of Health
  • FIG. 17 shows a method 1700 that includes processing at least one section of the at least one audio signal to determine at least one speech pattern of the patient, as indicated at 1504, and in addition, comparing the at least one speech pattern with at least one previous speech pattern of the patient to determine whether the patient has complied with the prescribed treatment regimen, as indicated at 1702.
  • the at least one previous speech pattern is representative of a speech pattern of the patient prior to initiation of treatment of the brain-related disorder, as indicated at 1704; a speech pattern of the patient after initiation of treatment of the brain-related disorder, as indicated at 1706; a speech pattern of the patient during known compliance of the patient with a treatment of the brain-related disorder, as indicated at 1708; or a speech pattern of the patient during treatment with a specified treatment regimen, as indicated at 1710.
  • a method 1800 includes processing at least one section of the at least one audio signal to determine at least one speech pattern of the patient, as indicated at 1504, and in addition, comparing the at least one speech pattern with a plurality of speech patterns and determining which of the plurality of speech patterns best matches the at least one speech pattern, as indicated at 1802.
  • the plurality of speech patterns includes stored prior speech patterns of the patient, the prior speech patterns representative of speech patterns of the patient with different treatment regimens, as indicated at 1804.
  • the plurality of speech patterns includes stored population speech patterns representative of speech patterns of populations of patients, as indicated at 1806.
  • At least one of the population speech patterns is representative of speech patterns of a population of patients without a brain-related disorder, as indicated at 1808; a population of patients having an untreated brain-related disorder, as indicated at 1810; or a population of patients having a brain-related disorder stabilized by treatment, as indicated at 1812.
  • the plurality of population speech patterns includes speech patterns representative of populations of patients undergoing different treatment regimens for a brain-related disorder, as indicated at 1814.
  • methods as described herein may be performed according to instructions implementable in hardware, software, and/or firmware. Such instructions may be stored in non-transitory machine -readable data storage media, for example.
  • Such instructions may be stored in non-transitory machine -readable data storage media, for example.
  • logic and similar implementations may include software or other control structures.
  • Electrical circuitry may have one or more paths of electrical current constructed and arranged to implement various functions as described herein.
  • one or more media may be configured to bear a device-detectable implementation when such media hold or transmit device detectable instructions operable to perform as described herein.
  • implementations may include an update or modification of existing software or firmware, or of gate arrays or programmable hardware, such as by performing a reception of or a transmission of one or more instructions in relation to one or more operations described herein.
  • an update or modification of existing software or firmware, or of gate arrays or programmable hardware such as by performing a reception of or a transmission of one or more instructions in relation to one or more operations described herein.
  • an update or modification of existing software or firmware or of gate arrays or programmable hardware, such as by performing a reception of or a transmission of one or more instructions in relation to one or more operations described herein.
  • an update or modification of existing software or firmware or of gate arrays or programmable hardware
  • implementation may include special-purpose hardware, software, firmware components, and/or general-purpose components executing or otherwise invoking special-purpose components.
  • Implementations may include executing a special -purpose instruction sequence or invoking circuitry for enabling, triggering, coordinating, requesting, or otherwise causing one or more occurrences of virtually any functional operations described herein.
  • operational or other logical descriptions herein may be expressed as source code and compiled or otherwise invoked as an executable instruction sequence.
  • implementations may be provided, in whole or in part, by source code, such as C++, or other code sequences.
  • source or other code implementation may be compiled/ /implemented/translated/converted into a high-level descriptor language (e.g., initially implementing described technologies in C or C++ programming language and thereafter converting the programming language implementation into a logic-synthesizable language implementation, a hardware description language implementation, a hardware design simulation implementation, and/or other such similar mode(s) of expression).
  • a high-level descriptor language e.g., initially implementing described technologies in C or C++ programming language and thereafter converting the programming language implementation into a logic-synthesizable language implementation, a hardware description language implementation, a hardware design simulation implementation, and/or other such similar mode(s) of expression.
  • a logical expression e.g., computer programming language implementation
  • a Verilog-type hardware description e.g., via Hardware Description Language (HDL) and/or Very High Speed Integrated Circuit Hardware Descriptor Language (VHDL)
  • VHDL Very High Speed Integrated Circuit Hardware Descriptor Language
  • Examples of a signal bearing medium include, but are not limited to non-transitory machine-readable data storage media such as a recordable type medium such as a floppy disk, a hard disk drive, a Compact Disc (CD), a Digital Video Disk (DVD), a digital tape, a computer memory, etc..
  • a signal bearing medium may also include transmission type medium such as a digital and/or an analog communication medium (e.g., a fiber optic cable, a waveguide, a wired communications link, a wireless communication link (e.g., transmitter, receiver, transmission logic, reception logic, etc.) and so forth).
  • FIG. 19 is a block diagram of a computer program product 1900 for implementing a method as described in connection with FIG. 9.
  • Computer program product 1900 includes a signal-bearing medium 1902 bearing: one or more instructions for sensing at least one audio signal including spontaneous speech from a patient with at least one audio sensor at a patient location, the patient having a brain-related disorder and a prescribed treatment regimen for treating at least one aspect of the brain-related disorder; one or more instructions for detecting spontaneous speech of the patient in the at least one audio signal with signal processing circuitry at the patient location; one or more instructions for generating with the signal processing circuitry speech data including data indicative of whether the patient has complied with the prescribed treatment regimen; and one or more instructions for transmitting a speech data signal containing the speech data including data indicative of whether the patient has complied with the prescribed treatment regimen to a receiving device at a monitoring location with at least one transmitting device at the patient location, as indicated at 1904.
  • Signal-bearing medium 1902 may be, for example, a computer-readable medium 1906,
  • FIG. 20 is a block diagram of a system 2000 for implementing a method as described in connection with FIG. 9.
  • System 2000 includes a computing device 2002 and instructions that when executed on the computing device cause the computing device to sense at least one audio signal including spontaneous speech from a patient with at least one audio sensor at a patient location, the patient having a brain-related disorder and a prescribed treatment regimen for treating at least one aspect of the brain-related disorder; detect spontaneous speech of the patient in the at least one audio signal with signal processing circuitry at the patient location; generate with the signal processing circuitry speech data including data indicative of whether the patient has complied with the prescribed treatment regimen; and transmit a speech data signal containing the speech data including data indicative of whether the patient has complied with the prescribed treatment regimen to a receiving device at a monitoring location with at least one transmitting device at the patient location, as indicated at 2004.
  • System 2000 may be, for example, a cell phone configured with application software 2006, a computing system or device 2008, a microprocessor-based system 2010, and/or a stand-alone
  • FIG. 21 is a flow diagram of a method 2100 of monitoring compliance of a patient with a prescribed treatment regimen, including method aspects occurring at or associated with a monitoring location, e.g., monitoring location 112 in FIG. 1.
  • Method 2100 includes receiving a speech data signal with a receiving device at a monitoring location, the speech data signal transmitted to the monitoring location from a patient location, the speech data signal containing speech data, the speech data including patient speech data representing spontaneous speech sensed from a patient by at least one audio sensor at a patient location, and the patient having a brain-related disorder and a prescribed treatment regimen for treating at least one aspect of the brain-related disorder, as indicated at 2102; identifying with speech identification circuitry patient speech data corresponding to speech from the patient in the speech data, the patient speech data including data indicative of at least one patient speech pattern, as indicated at 2104; determining with compliance determination circuitry whether the patient has complied with the prescribed treatment regimen based on whether the patient speech data includes data indicative of the at least one patient speech pattern matching at least one characteristic speech pattern,
  • FIGS. 22 - 32 depict variations and expansions of method 2100 as shown in FIG. 21.
  • steps 2102 - 2108 are as described generally in connection with FIG. 21.
  • method steps outlined with dashed lines represent steps that are included in some, but not all method aspects, and combinations of steps other than those specifically depicted in the figures are possible as would be known by those having ordinary skill in the relevant art.
  • a method 2200 includes receiving a signal indicative of initiation of treatment of the patient according to the treatment regimen and beginning to receive the speech data signal with the receiving device responsive to receipt of the signal indicative of initiation of treatment of the patient, as indicated at 2202.
  • a method 2300 includes performing
  • method 2300 includes performing intermittently at least one of receiving the speech data with the receiving device, identifying the patient speech data, determining whether the patient has complied with the prescribed treatment regimen and reporting with the reporting circuitry, as indicated at 2304.
  • method 2300 includes performing according to a schedule at least one of receiving the speech data with the receiving device, identifying the patient speech data, determining whether the patient has complied with the prescribed treatment regimen and reporting with the reporting circuitry, as indicated at 2306.
  • FIG. 24 depicts a method 2400, which includes determining a presence of the patient at the patient location with patient identification circuitry at the monitoring location from at least one identity signal received at the monitoring location from the patient location, wherein identifying with speech identification circuitry patient speech data corresponding to speech from the patient in the speech data signal includes identifying patient speech data based at least in part on the identity signal, as indicated at 2402.
  • the identity signal includes a voice signal, as indicated at 2404; an image signal, as indicated at 2406; a biometric signal, as indicated at 2408; an RFID signal, as indicated at 2410; or a cell phone identification signal, as indicated at 2412.
  • FIG. 24 includes a voice signal, as indicated at 2404; an image signal, as indicated at 2406; a biometric signal, as indicated at 2408; an RFID signal, as indicated at 2410; or a cell phone identification signal, as indicated at 2412.
  • method 2500 which includes one or more of separating patient speech data from speech data from other people, as indicated at 2502; storing prescription information in a data storage device, the prescription information indicative of the prescribed treatment regimen, as indicated at 2504; receiving prescription information indicative of the prescribed treatment regimen, as indicated at 2506; and suggesting to the patient the treatment regimen for treating at least one aspect of the brain-related disorder, as indicated at 2508.
  • FIG. 26 depicts a method 2600, relating to determining patient compliance based on whether the time course of the patient's response to a treatment regimen matches an expected time course.
  • method 2600 includes determining a time at which the spontaneous speech represented by the patient speech data was detected from the patient relative to a delivery time at which a treatment regimen was delivered to a patient, comparing the determined time with an expected time for occurrence of the characteristic speech pattern in a subject in response to delivery of the treatment regimen to the subject, and determining whether the patient has complied with the prescribed treatment regimen based in part on whether the determined time matches the expected time, as indicated at 2602.
  • receiving the speech data signal includes receiving a wireless signal, as indicated at 2604; receiving data via a computer network connection, as indicated at 2606; receiving data from a USB device, as indicated at 2608; and/or receiving data from a data storage device, as indicated at 2610.
  • FIG. 27 depicts method 2700 including steps 2102 - 2108 as shown in FIG. 21, and including additional steps relating to comparison of a patient's speech patterns with multiple characteristic speech patterns.
  • at least one of identifying with speech identification circuitry patient speech data corresponding to speech from the patient in the speech data and determining with compliance determination circuitry whether the patient has complied with the prescribed treatment regimen includes analyzing the speech data with a speech processor, as indicated at 2702.
  • At least one of identifying with speech identification circuitry patient speech data corresponding to speech from the patient in the speech data and determining with compliance determination circuitry whether the patient has complied with the prescribed treatment regimen includes analyzing the patient speech data to determine the patient speech pattern from the patient speech data, and comparing the patient speech pattern with the at least one characteristic speech pattern, as indicated at 2704. In an aspect, comparing the patient speech pattern with the at least one
  • method 2700 includes comparing the patient speech pattern with a plurality of characteristic speech patterns, as indicated at 2706.
  • method 2700 may include determining which of the plurality of characteristic speech patterns best matches the patient speech pattern, as indicated at 2708.
  • method 2700 also includes determining a level of compliance of the patient with the prescribed treatment regimen based on which of the plurality of characteristic speech patterns best matches the patient speech pattern, wherein the plurality of characteristic speech patterns includes a plurality of previous speech patterns of the patient each representative of a speech pattern of the patient at a different level of compliance of the patient with prescribed treatment regimen, and wherein the characteristic speech pattern that best matches the patient speech pattern indicates the level of compliance of the patient with the prescribed treatment regimen, as indicated at 2710.
  • Method 2700 may also include determining a level of compliance of the patient with the prescribed treatment regimen based on which of the plurality of characteristic speech patterns best matches the patient speech pattern, wherein the plurality of characteristic speech patterns includes a plurality of population speech patterns, each population speech pattern representative of a typical speech pattern for a population of patients at a different level of compliance with the prescribed treatment regimen, and wherein the characteristic speech pattern that best matches the patient speech pattern indicates the level of compliance of the patient with the prescribed treatment regimen, as indicated at 2712.
  • FIG. 28 depicts method 2800 including steps 2102 - 2108 as shown in FIG. 21.
  • at least one of identifying with speech identification circuitry patient speech data in the speech data and determining with compliance determination circuitry whether the patient has complied with the prescribed treatment regimen includes comparing the patient speech data with characteristic speech data indicative of the characteristic speech pattern, as indicated at 2802.
  • comparing the speech data with the characteristic speech data indicative of the characteristic speech pattern includes comparing the patient speech data with a plurality of characteristic speech data sets, each said characteristic speech data set indicative of a characteristic speech pattern, indicated at 2804.
  • method 2800 also includes determining which of the plurality of characteristic speech data sets best matches the patient speech data, as indicated at 2806.
  • each said characteristic speech data set corresponds to a stored speech pattern representative of the patient undergoing a distinct treatment regimen, as indicated at 2808, or to a stored speech pattern
  • method 2800 includes identifying a treatment regimen associated with the characteristic speech data set that best matches the patient speech data, as indicated at 2812.
  • FIG. 29 depicts method 2900, in which, in various aspects, reporting with reporting circuitry a conclusion based on the determination of whether the patient has complied with the prescribed treatment regimen includes displaying a report on a display device, as indicated at 2902; generating a notification, as indicated at 2904; transmitting a notification to a wireless device, as indicated at 2906; generating an audio alarm, as indicated at 2908; or storing a notification in a data storage device, as indicated at 2910.
  • Generating an audio alarm may involve generating a beeping or chiming sound, for example, or generating a voice alarm (e.g., a warning or notification) from recorded or synthesized speech, e.g., to deliver a verbal warning to the medical care provider at the monitoring location.
  • a voice alarm e.g., a warning or notification
  • determining with compliance determination circuitry whether the patient has complied with the prescribed treatment regimen includes determining that the patient has failed to comply with the prescribed treatment regimen, as indicated at 2912; determining that the patient has complied with the prescribed treatment regimen, as indicated at 2914; and/or determining a level of compliance of the patient with the prescribed treatment regimen, as indicated at 2916.
  • Approaches for determining compliance, lack of compliance, or level of compliance are discussed herein above.
  • FIG. 30 depicts method 3000, wherein the brain-related disorder is schizophrenia, as indicated at 3002; Parkinson's disease, as indicated at 3004; an Autism Spectrum Disorder, as indicated at 3006; dementia, as indicated at 3008; Bipolar Disorder, as indicated at 3010; or depression, as indicated at 3012. Other brain-related disorders, as discussed herein, may be monitored.
  • the brain-related disorder is schizophrenia, as indicated at 3002; Parkinson's disease, as indicated at 3004; an Autism Spectrum Disorder, as indicated at 3006; dementia, as indicated at 3008; Bipolar Disorder, as indicated at 3010; or depression, as indicated at 3012.
  • Other brain-related disorders, as discussed herein, may be monitored.
  • the at least one characteristic speech pattern includes at least one previous speech pattern of the patient, as indicated at 3102.
  • the at least one previous speech pattern is representative of a speech pattern of the patient prior to initiation of treatment of the brain- related disorder, as indicated at 3104; a speech pattern of the patient after initiation of treatment of the brain-related disorder, as indicated at 3106; a speech pattern of the patient during known compliance of the patient with a treatment of the brain-related disorder, as indicated at 3108; or a speech pattern of the patient during treatment at a specified treatment regimen, as indicated at 3110.
  • Comparison of a patient speech pattern to one or more characteristic speech patterns is discussed herein above.
  • the at least one characteristic speech pattern includes at least one population speech pattern representative of a typical speech pattern of a population of patients, as indicated at 3202.
  • the at least one population speech pattern is representative of speech patterns of a population without the brain-related disorder, as indicated at 3204; speech patterns of an untreated population with the brain-related disorder, as indicated at 3206; or speech patterns of a population having the brain-related disorder stabilized by a treatment regimen, as indicated at 3208.
  • FIG. 33 depicts a computer program product 3300, for implementing the method of FIG. 22.
  • Computer program product 3300 includes a signal-bearing medium 3302 bearing one or more instructions for receiving a speech data signal with a receiving device at a monitoring location, the speech data signal transmitted to the monitoring location from a patient location, the speech data signal containing speech data, the speech data including patient speech data representing spontaneous speech sensed from a patient by at least one audio sensor at a patient location, and the patient having a brain-related disorder and a prescribed treatment regimen for treating at least one aspect of the brain-related disorder, one or more instructions identifying with speech identification circuitry patient speech data corresponding to speech from the patient in the speech data, the patient speech data including data indicative of at least one patient speech pattern, one or more instructions for determining with compliance determination circuitry whether the patient has complied with the prescribed treatment regimen based on whether the patient speech data includes data indicative of the at least one patient speech pattern matching at least one
  • Signal-bearing medium 3302 may be, for example, a computer-readable medium 3306, a recordable medium 3308, a non- transitory signal-bearing medium 3310, or a communications medium 3312.
  • FIG. 34 depicts a system 3400 for implementing the method of FIG. 22.
  • System 3400 includes a computing device 3402 and instructions that when executed on computing device 3402 cause computing device 3402 to receive a speech data signal with a receiving device at a monitoring location, the speech data signal transmitted to the monitoring location from a patient location, the speech data signal containing speech data, the speech data including patient speech data representing spontaneous speech sensed from a patient by at least one audio sensor at a patient location, and the patient having a brain-related disorder and a prescribed treatment regimen for treating at least one aspect of the brain- related disorder; identify with speech identification circuitry patient speech data corresponding to speech from the patient in the speech data, the patient speech data including data indicative of at least one patient speech pattern; determine with compliance determination circuitry whether the patient has complied with the prescribed treatment regimen based on whether the patient speech data includes data indicative of the at least one patient speech pattern matching at least one characteristic speech pattern; and report with reporting circuitry a conclusion based on the determination of whether the patient has complied with the prescribed treatment regimen, as indicated at 3404.
  • System 3400 may be, for example, a cell phone configured
  • any two components so associated can also be viewed as being “operably connected”, or “operably coupled,” to each other to achieve the desired functionality, and any two components capable of being so associated can also be viewed as being “operably couplable,” to each other to achieve the desired functionality.
  • operably couplable include but are not limited to physically mateable and/or physically interacting components, and/or wirelessly interactable, and/or wirelessly interacting components, and/or logically interacting, and/or logically interactable components.
  • one or more components may be referred to herein as
  • a system comprising:
  • At least one receiving device for use at a monitoring location for receiving a speech data signal transmitted to the monitoring location from a patient location, the speech data signal containing speech data, the speech data including patient speech data representing spontaneous speech sensed from a patient with at least one audio sensor at the patient location, and the patient having a brain-related disorder and a prescribed treatment regimen for treating at least one aspect of the brain-related disorder;
  • speech identification circuitry configured to identify the patient speech data corresponding to speech from the patient in the speech data, the patient speech data including data indicative of at least one patient speech pattern;
  • compliance determination circuitry configured to determine compliance of the patient with the prescribed treatment regimen based on whether the patient speech data includes data indicative of the at least one patient speech pattern matching at least one characteristic speech pattern;
  • reporting circuitry configured to report a conclusion based on the determination of whether the patient has complied with the prescribed treatment regimen.
  • control circuitry for controlling at least one of the at least one receiving device, the speech identification circuitry, the compliance determination circuitry, and the reporting circuitry.
  • the speech identification circuitry includes: patient identification circuitry configured to determine a presence of the patient from at least one identity signal received at the monitoring location from the patient location;
  • the speech identification circuitry is configured to identify patient speech data corresponding to speech from the patient in the speech data based at least in part on the determination of the presence of the patient by the patient identification circuitry.
  • the identity signal includes at least a portion of the speech data signal
  • the patient identification circuitry is configured to analyze the speech data signal to determine the presence of the patient by identifying at least a portion of the speech data signal that resembles a known speech data signal of the patient, and wherein the speech identification circuitry is configured to identify patient speech data by identifying speech data corresponding to the presence of the patient.
  • the identity signal includes an image signal received from an imaging device at the patient location, wherein the patient identification circuitry is configured to analyze the image signal to determine the presence of the patient, and wherein the speech identification circuitry is configured to identify patient speech data by identifying speech data corresponding to the presence of the patient detected from the image signal.
  • the identity signal includes a biometric signal from at least one biometric sensor at the patient location, wherein the patient identification circuitry is configured to analyze the biometric signal to determine the presence of the patient, and wherein the speech identification circuitry is configured to identify patient speech data by identifying speech data corresponding to the presence of the patient detected from the biometric signal .
  • the authentication factor is selected from the group consisting of a security token, a password, a digital signature, and a
  • cell phone identification code is selected from the group consisting of an electronic serial number, a mobile identification number, and a system identification code.
  • an input device for receiving prescription information indicative of the treatment regimen prescribed to the patient.
  • At least one data storage device for storing prescription information indicative of the treatment regimen prescribed to the patient.
  • the at least one receiving device includes a computer drive.
  • at least one of the speech identification circuitry and the compliance determination circuitry includes a speech processor.
  • a speech processor for analyzing the patient speech data to determine the at least one patient speech pattern
  • a comparator for comparing the at least one patient speech pattern with the at least one characteristic speech pattern.
  • a comparator for comparing the patient speech data with a characteristic speech data set indicative of the characteristic speech pattern.
  • reporting circuitry includes a display device.
  • reporting circuitry includes circuitry for generating a notification.
  • reporting circuitry includes circuitry for transmitting a notification to a wireless device.
  • reporting circuitry includes circuitry for generating an audio alarm.
  • reporting circuitry includes circuitry for storing a notification in a data storage device.
  • the speech data signal receiving a speech data signal with a receiving device at a monitoring location, the speech data signal transmitted to the monitoring location from a patient location, the speech data signal containing speech data, the speech data including patient speech data representing spontaneous speech sensed from a patient by at least one audio sensor at the patient location, and the patient having a brain-related disorder and a prescribed treatment regimen for treating at least one aspect of the brain-related disorder;
  • patient speech data corresponding to speech from the patient in the speech data, the patient speech data including data indicative of at least one patient speech pattern
  • reporting with reporting circuitry a conclusion based on the determination of whether the patient has complied with the prescribed treatment regimen.
  • identifying with speech identification circuitry patient speech data corresponding to speech from the patient in the speech data signal includes identifying patient speech data based at least in part on the identity signal.
  • prescription information in a data storage device, the prescription information indicative of the prescribed treatment regimen.
  • receiving the speech data signal includes receiving a wireless signal.
  • receiving the speech data signal includes receiving data via a computer network connection.
  • receiving the speech data signal includes receiving data from a USB device.
  • receiving the speech data signal includes receiving data from a data storage device.
  • comparing the patient speech pattern with the at least one characteristic speech pattern includes comparing the patient speech pattern with a plurality of characteristic speech patterns.
  • the plurality of characteristic speech patterns includes a plurality of previous speech patterns of the patient each representative of a speech pattern of the patient at a different level of compliance of the patient with the prescribed treatment regimen, and wherein the characteristic speech pattern that best matches the patient speech pattern indicates the level of compliance of the patient with the prescribed treatment regimen.
  • the plurality of characteristic speech patterns includes a plurality of population speech patterns, each population speech pattern representative of a typical speech pattern for a population of patients at a different level of compliance with the prescribed treatment regimen, and wherein the characteristic speech pattern that best matches the patient speech pattern indicates the level of compliance of the patient with the prescribed treatment regimen.
  • comparing the speech data with the characteristic speech data indicative of the characteristic speech pattern includes comparing the patient speech data with a plurality of characteristic speech data sets, each said characteristic speech data set indicative of a characteristic speech pattern.
  • each said characteristic speech data set corresponds to a stored speech pattern representative of the patient undergoing a distinct treatment regimen.
  • each said characteristic speech data set corresponds to a stored speech pattern representative of a population of patients undergoing a distinct treatment regimen.
  • reporting a conclusion based on the determination of whether the patient has complied with the prescribed treatment regimen includes displaying a report on a display device.
  • reporting a conclusion based on the determination of whether the patient has complied with the prescribed treatment regimen includes generating a notification.
  • reporting a conclusion based on the determination of whether the patient has complied with the prescribed treatment regimen includes transmitting a notification to a wireless device.
  • reporting a conclusion based on the determination of whether the patient has complied with the prescribed treatment regimen includes generating an audio alarm.
  • reporting a conclusion based on the determination of whether the patient has complied with the prescribed treatment regimen includes storing a notification in a data storage device.
  • determining with compliance determination circuitry whether the patient has complied with the prescribed treatment regimen includes determining that the patient has failed to comply with the prescribed treatment regimen.
  • determining with compliance determination circuitry whether the patient has complied with the prescribed treatment regimen includes determining that the patient has complied with the prescribed treatment regimen.
  • determining with compliance determination circuitry whether the patient has complied with the prescribed treatment regimen includes determining a level of compliance of the patient with the prescribed treatment regimen.
  • the at least one characteristic speech pattern includes at least one population speech pattern representative of a typical speech pattern of a population of patients.
  • the at least one population speech pattern is representative of speech patterns of an untreated population with the brain-related disorder.
  • the at least one population speech pattern is representative of speech patterns of a population having the brain-related disorder stabilized by a treatment regimen.
  • a computer program product comprising:
  • one or more instructions for performing according to a schedule at least one of receiving the speech data with the receiving device, identifying the patient speech data, determining whether the patient has complied with the prescribed treatment regimen and reporting with the reporting circuitry.
  • non-transitory signal-bearing medium bears one or more instructions for determining a presence of the patient at the patient location, with patient identification circuitry at the monitoring location, from at least one identity signal received at the monitoring location from the patient location;
  • identifying with speech identification circuitry patient speech data corresponding to speech from the patient in the speech data signal includes identifying patient speech data based at least in part on the identity signal.
  • one or more instructions for receiving prescription information indicative of the prescribed treatment regimen are one or more instructions for receiving prescription information indicative of the prescribed treatment regimen.
  • one or more instructions for suggesting to the patient the prescribed treatment regimen for treating at least one aspect of the brain-related disorder are provided.
  • the computer program product of clause 88 wherein the one or more instructions for receiving the speech data signal with the receiving device include one or more instructions for receiving data from a data storage device. 108. The computer program product of clause 88, wherein at least one of the one or more instructions for identifying with speech identification circuitry patient speech data corresponding to speech from the patient in the speech data and the one or more instructions for determining with compliance determination circuitry whether the patient has complied with the prescribed treatment regimen include one or more instructions for analyzing the speech data with a speech processor.
  • one or more instructions for comparing the patient speech pattern with the at least one characteristic speech pattern are provided.
  • non-transitory signal-bearing medium bears one or more instructions for determining a level of compliance of the patient with the prescribed treatment regimen based on which of the plurality characteristic speech patterns best matches the patient speech pattern; wherein the plurality of characteristic speech patterns includes a plurality of previous speech patterns of the patient each representative of a speech pattern of the patient at a different level of compliance of the patient with the prescribed treatment regimen, and wherein the characteristic speech pattern that best matches the patient speech pattern indicates the level of compliance of the patient with the prescribed treatment regimen.
  • non-transitory signal-bearing medium bears one or more instructions for determining a level of compliance of the patient with the prescribed treatment regimen based on which of the plurality of characteristic speech patterns best matches the patient speech pattern; wherein the plurality of characteristic speech patterns includes a plurality of population speech patterns, each population speech pattern representative of a typical speech pattern for a population of patients at a different level of compliance with the prescribed treatment regimen, and wherein the characteristic speech pattern that best matches the patient speech pattern indicates the level of compliance of the patient with the prescribed treatment regimen.
  • one or more instructions for comparing the patient speech data with characteristic speech data indicative of the characteristic speech pattern are provided.
  • non-transitory signal bearing medium includes one or more instructions for determining which of the plurality of characteristic speech data sets best matches the patient speech data.
  • non-transitory signal bearing medium includes one or more instructions for identifying a treatment regimen associated with the characteristic speech data set that best matches the patient speech data.
  • determining with compliance determination circuitry whether the patient has complied with the prescribed treatment regimen include one or more instructions for determining a level of compliance of the patient with the prescribed treatment regimen.
  • a system comprising:
  • a speech data signal with a receiving device at a monitoring location, the speech data signal transmitted to the monitoring location from a patient location, the speech data signal containing speech data, the speech data including patient speech data representing spontaneous speech sensed from a patient by at least one audio sensor at a patient location, and the patient having a brain-related disorder and a prescribed treatment regimen for treating at least one aspect of the brain-related disorder; identify with speech identification circuitry patient speech data corresponding to speech from the patient in the speech data, the patient speech data including data indicative of at least one patient speech pattern;
  • report with reporting circuitry a conclusion based on the determination of whether the patient has complied with the prescribed treatment regimen.
  • a system comprising:
  • At least one audio sensor for sensing at least one audio signal
  • spontaneous speech from a patient at a patient location the patient having a brain-related disorder and a prescribed treatment regimen for treating at least one aspect of the brain- related disorder;
  • At least one transmitting device for transmitting a speech data signal containing the speech data including data indicative of whether the patient has complied with the prescribed treatment regimen from the patient location to a receiving device at a monitoring location.
  • the signal processing circuitry includes: patient identification circuitry configured to determine a presence of the patient from at least one identity signal sensed at the patient location;
  • the signal processing circuitry is configured to detect the spontaneous speech from the patient based at least in part on the determination of the presence of the patient by the patient identification circuitry.
  • control circuitry for controlling at least one of the at least one audio sensor, the signal processing circuitry, and the at least one transmitting device.
  • the at least one identity signal includes at least a portion of the at least one audio signal
  • the patient identification circuitry is configured to analyze the at least one audio signal to determine the presence of the patient by identifying at least a portion of the at least one audio signal that resembles known speech of the patient
  • the signal processing circuitry is configured to detect the spontaneous speech from the patient by identifying speech data corresponding to presence of the patient detected from the at least one audio signal.
  • the at least one identity signal includes an image signal received from an imaging device at the patient location, wherein the patient identification circuitry is configured to analyze the image signal to determine the presence of the patient, and wherein the signal processing circuitry is configured to detect the spontaneous speech from the patient by identifying speech data corresponding to presence of the patient detected from the image signal.
  • the at least one identity signal includes a biometric signal from at least one biometric sensor at the patient location, wherein the patient identification circuitry is configured to analyze the biometric signal to determine the presence of the patient, and wherein the signal processing circuitry is configured to detect the spontaneous speech from the patient by identifying the speech data
  • the cell phone identification code is selected from the group consisting of an electronic serial number, a mobile identification number, and a system identification code.
  • the at least one identity signal includes an RFID signal.
  • the signal processing circuitry includes a comparator for comparing the at least one speech pattern of the patient with at least one characteristic speech pattern to determine whether the patient has complied with the prescribed treatment regimen.
  • the signal processing circuitry includes a comparator for comparing the at least one speech parameter of the patient with at least one characteristic speech parameter to determine whether the patient has complied with the prescribed treatment regimen.
  • notification circuitry for generating a notification.
  • the notification circuitry includes circuitry for generating a notification to be transmitted to a wireless device.
  • the notification circuitry includes circuitry for storing a notification in a data storage device.
  • a method comprising:
  • At least one audio signal including spontaneous speech from a patient with at least one audio sensor at a patient location the patient having a brain-related disorder and a prescribed treatment regimen for treating at least one aspect of the brain-related disorder;
  • detecting the spontaneous speech of the patient in the at least one audio signal with the signal processing circuitry at the patient location includes detecting speech from the patient based at least in part on the determination of the presence of the patient by the patient identification circuitry.
  • transmitting the speech data signal includes transmitting a wireless signal.
  • transmitting the speech data signal includes transmitting a signal via the internet.
  • time data to the receiving device with the at least one transmitting device at the patient location, the time data representing a time at which the spontaneous speech was detected.
  • processing the at least one audio signal to exclude at least one portion of the at least one audio signal that does not contain the spontaneous speech of the patient.
  • the speech data includes the at least one speech parameter.
  • a computer program product comprising:
  • one or more instructions for sensing at least one audio signal including
  • spontaneous speech from a patient with at least one audio sensor at a patient location the patient having a brain-related disorder and a prescribed treatment regimen for treating at least one aspect of the brain-related disorder;
  • one or more instructions for generating with the signal processing circuitry speech data including data indicative of whether the patient has complied with the prescribed treatment regimen
  • non-transitory signal-bearing medium bears one or more instructions for performing substantially continuously at least one of sensing the at least one audio signal, detecting the spontaneous speech of the patient, generating the speech data, and transmitting the speech data signal.
  • non-transitory signal-bearing medium bears one or more instructions for performing intermittently at least one of sensing the at least one audio signal, detecting the spontaneous speech of the patient, generating the speech data, and transmitting the speech data signal.
  • non-transitory signal-bearing medium bears one or more instructions for performing, according to a schedule, at least one of sensing the at least one audio signal, detecting the spontaneous speech of the patient, generating the speech data, and transmitting the speech data signal.
  • non-transitory signal-bearing medium bears one or more instructions for determining a presence of the patient with patient identification circuitry based on at least one identity signal sensed at the patient location; wherein detecting the spontaneous speech of the patient in the at least one audio signal with the signal processing circuitry at the patient location includes detecting speech from the patient based at least in part on the determination of the presence of the patient by the patient identification circuitry.
  • non-transitory signal-bearing medium bears one or more instructions for processing the at least one audio signal to exclude at least one portion of the at least one audio signal that does not contain the spontaneous speech of the patient.
  • the non-transitory signal-bearing medium bears one or more instructions for transmitting the speech data signal to the receiving device at the monitoring location with the at least one transmitting device at the patient location if the speech data is indicative of the patient not complying with the prescribed treatment regimen.
  • one or more instructions for determining which of the plurality of speech patterns best matches the at least one speech pattern are provided.
  • a system comprising:
  • At least one audio signal including spontaneous speech from a patient with at least one audio sensor at a patient location, the patient having a brain-related disorder and a prescribed treatment regimen for treating at least one aspect of the brain-related disorder; detect the spontaneous speech of the patient in the at least one audio signal with signal processing circuitry at the patient location;

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Abstract

La présente invention concerne des procédés et des systèmes de surveillance de parole chez un patient afin de déterminer la conformité du patient avec un régime prescrit pour le traitement lié à un trouble associé au cerveau. La parole chez un patient est détectée avec un capteur audio au niveau de l'emplacement du patient, et des données de parole sont transmises à un emplacement de surveillance. La capteur audio et d'autres éléments au niveau de l'emplacement du patient peuvent être incorporés dans, ou associés avec, un téléphone cellulaire, un système informatique, ou un dispositif à base de microprocesseurs autonomes, par exemple. La parole chez un patient est traitée au niveau de l'emplacement du patient et/ou de l'emplacement de surveillance pour identifier des paramètres de parole et/ou des motifs qui indiquent si le patient est en conformité avec le régime de traitement prescrit. L'identité du patient peut être déterminée par identification biométrique ou d'autres techniques d'authentification. Le système peut fournir un rapport à un tiers intéressé, par exemple un fournisseur de soins médicaux, selon que (et/ou l'étendue à laquelle) le patient est en conformité avec le régime de traitement prescrit. Le système de surveillance peut transmettre un rapport à un dispositif sans fil, tel qu'un système de radiorecherche ou un téléphone mobile, générer une alarme ou une notification, et/ou stocker des informations pour une utilisation ultérieure.
PCT/US2015/060803 2014-11-17 2015-11-16 Surveillance de conformité de traitement à l'aide de formes de parole capturées passivement à partir d'un environnement de patient Ceased WO2016081339A1 (fr)

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HK18102865.8A HK1243519A1 (zh) 2014-11-17 2015-11-16 使用从患者环境中被动捕获的语音模式来监测治疗遵从性
EP15861246.5A EP3221839A4 (fr) 2014-11-17 2015-11-16 Surveillance de conformité de traitement à l'aide de formes de parole capturées passivement à partir d'un environnement de patient
CN201580062375.3A CN107111672A (zh) 2014-11-17 2015-11-16 使用从患者环境中被动捕获的语音模式来监测治疗遵从性
IL252279A IL252279A0 (en) 2014-11-17 2017-05-15 Monitoring compliance to treatment using speech patterns passively picked up from a patient's environment

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US14/543,066 US9585616B2 (en) 2014-11-17 2014-11-17 Determining treatment compliance using speech patterns passively captured from a patient environment
US14/543,066 2014-11-17
US14/543,030 US9589107B2 (en) 2014-11-17 2014-11-17 Monitoring treatment compliance using speech patterns passively captured from a patient environment
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