WO2023125478A1 - Appareil d'interface cerveau-ordinateur et procédé d'acquisition d'informations - Google Patents

Appareil d'interface cerveau-ordinateur et procédé d'acquisition d'informations Download PDF

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WO2023125478A1
WO2023125478A1 PCT/CN2022/142182 CN2022142182W WO2023125478A1 WO 2023125478 A1 WO2023125478 A1 WO 2023125478A1 CN 2022142182 W CN2022142182 W CN 2022142182W WO 2023125478 A1 WO2023125478 A1 WO 2023125478A1
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sensing
brain
light
computer interface
pulse
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Chinese (zh)
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陆晓风
李良川
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Huawei Technologies Co Ltd
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Huawei Technologies Co Ltd
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0033—Features or image-related aspects of imaging apparatus, e.g. for MRI, optical tomography or impedance tomography apparatus; Arrangements of imaging apparatus in a room
    • A61B5/004—Features or image-related aspects of imaging apparatus, e.g. for MRI, optical tomography or impedance tomography apparatus; Arrangements of imaging apparatus in a room adapted for image acquisition of a particular organ or body part
    • A61B5/0042—Features or image-related aspects of imaging apparatus, e.g. for MRI, optical tomography or impedance tomography apparatus; Arrangements of imaging apparatus in a room adapted for image acquisition of a particular organ or body part for the brain
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0059—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
    • A61B5/0075—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence by spectroscopy, i.e. measuring spectra, e.g. Raman spectroscopy, infrared absorption spectroscopy
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
    • G01D5/00—Mechanical means for transferring the output of a sensing member; Means for converting the output of a sensing member to another variable where the form or nature of the sensing member does not constrain the means for converting; Transducers not specially adapted for a specific variable
    • G01D5/26—Mechanical means for transferring the output of a sensing member; Means for converting the output of a sensing member to another variable where the form or nature of the sensing member does not constrain the means for converting; Transducers not specially adapted for a specific variable characterised by optical transfer means, i.e. using infrared, visible, or ultraviolet light
    • G01D5/32—Mechanical means for transferring the output of a sensing member; Means for converting the output of a sensing member to another variable where the form or nature of the sensing member does not constrain the means for converting; Transducers not specially adapted for a specific variable characterised by optical transfer means, i.e. using infrared, visible, or ultraviolet light with attenuation or whole or partial obturation of beams of light
    • G01D5/34—Mechanical means for transferring the output of a sensing member; Means for converting the output of a sensing member to another variable where the form or nature of the sensing member does not constrain the means for converting; Transducers not specially adapted for a specific variable characterised by optical transfer means, i.e. using infrared, visible, or ultraviolet light with attenuation or whole or partial obturation of beams of light the beams of light being detected by photocells
    • G01D5/353—Mechanical means for transferring the output of a sensing member; Means for converting the output of a sensing member to another variable where the form or nature of the sensing member does not constrain the means for converting; Transducers not specially adapted for a specific variable characterised by optical transfer means, i.e. using infrared, visible, or ultraviolet light with attenuation or whole or partial obturation of beams of light the beams of light being detected by photocells influencing the transmission properties of an optical fibre
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
    • G01D5/00—Mechanical means for transferring the output of a sensing member; Means for converting the output of a sensing member to another variable where the form or nature of the sensing member does not constrain the means for converting; Transducers not specially adapted for a specific variable
    • G01D5/26—Mechanical means for transferring the output of a sensing member; Means for converting the output of a sensing member to another variable where the form or nature of the sensing member does not constrain the means for converting; Transducers not specially adapted for a specific variable characterised by optical transfer means, i.e. using infrared, visible, or ultraviolet light
    • G01D5/32—Mechanical means for transferring the output of a sensing member; Means for converting the output of a sensing member to another variable where the form or nature of the sensing member does not constrain the means for converting; Transducers not specially adapted for a specific variable characterised by optical transfer means, i.e. using infrared, visible, or ultraviolet light with attenuation or whole or partial obturation of beams of light
    • G01D5/34—Mechanical means for transferring the output of a sensing member; Means for converting the output of a sensing member to another variable where the form or nature of the sensing member does not constrain the means for converting; Transducers not specially adapted for a specific variable characterised by optical transfer means, i.e. using infrared, visible, or ultraviolet light with attenuation or whole or partial obturation of beams of light the beams of light being detected by photocells
    • G01D5/36—Forming the light into pulses
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/011—Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
    • G06F3/015—Input arrangements based on nervous system activity detection, e.g. brain waves [EEG] detection, electromyograms [EMG] detection, electrodermal response detection
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04J—MULTIPLEX COMMUNICATION
    • H04J14/00—Optical multiplex systems
    • H04J14/08—Time-division multiplex systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04Q—SELECTING
    • H04Q11/00—Selecting arrangements for multiplex systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04Q—SELECTING
    • H04Q11/00—Selecting arrangements for multiplex systems
    • H04Q11/0001—Selecting arrangements for multiplex systems using optical switching
    • H04Q11/0062—Network aspects
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2576/00—Medical imaging apparatus involving image processing or analysis
    • A61B2576/02—Medical imaging apparatus involving image processing or analysis specially adapted for a particular organ or body part
    • A61B2576/026—Medical imaging apparatus involving image processing or analysis specially adapted for a particular organ or body part for the brain
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

Definitions

  • the embodiments of the present application relate to the field of the Internet of Things, and in particular to a brain-computer interface device and an information acquisition method.
  • Brain-Computer Interface has gradually become an important enabling technology for the future intelligent world in recent years.
  • the brain-computer interface has become an important part of its technology group.
  • Time resolution and spatial resolution are the main technical indicators of BCI.
  • functional near infrared technology functional near infrared, fNIR
  • fNIR usually uses a set of near-infrared emitting and receiving sensors to be responsible for the sensing of local brain regions, and several infrared receiving points are set around an infrared emitting point. Part of the infrared light that enters the brain through the skull is scattered by the brain tissue, exits backwards, and is received by the photodetector.
  • infrared lasers with different wavelengths can be used at each infrared transmitter, and parallel sensing communication channels are formed between different sensor points.
  • each sensor point of the above scheme uses a different wavelength, which requires the system to have a wavelength control mechanism. If the laser wavelength or temperature wavelength control is strictly controlled and selected, as the number of sensing points increases, the implementation cost of the system increases sharply, and Make the host computer scale of the system huge.
  • the embodiment of the present application provides a brain-computer interface device, which is used to realize high spatial resolution of the brain-computer interface on the basis of ensuring the miniaturization and integration of the brain-computer interface.
  • the embodiment of the present application also provides a corresponding information acquisition method.
  • the first aspect of the present application provides a brain-computer interface device, including a light source, a time domain delay module, a wavelength-dependent optical splitting module, a sensor network, and a sensor front end;
  • the light source is used to provide sensing detection light, and the sensing detection light includes multiple Broad-spectrum pulse trains, the repetition frequency of multiple broad-spectrum pulse trains is the first repetition rate, and each broad-spectrum pulse train is composed of multiple pulse lights of different wavelengths;
  • the time domain delay module is used to combine multiple broadband pulse trains
  • the pulse light train is converted into a plurality of multi-wave pulse light trains, each multi-wave pulse light train includes multiple pulse lights of different wavelengths, and the repetition frequency of multiple pulse lights of different wavelengths is the second repetition frequency, and the second repetition frequency is N times the first repetition frequency, N is the number of wavelength types of pulsed lights of multiple different wavelengths;
  • the wavelength-dependent optical splitting module is used to decompose multiple multi-wave pulsed light trains into N sparse pulsed light trains, each sparse pulse
  • the light source in this application is a wide-spectrum pulse light source
  • the time domain delay module can be an optical fiber delay line, a dispersion module or a dispersion waveguide, etc.
  • the wavelength-dependent optical splitting module is a splitter
  • the sensor network is a passive optical network (passive optical network, PON) ).
  • the brain-computer interface device in this application adopts functional infrared technology (fNIR), and fNIR has better temporal resolution, but insufficient spatial resolution.
  • fNIR functional infrared technology
  • This application is based on wavelength division-time division multiplexing technology and adopts a point-to-multipoint PON network architecture, which greatly improves the spatial density of the sensing point layout, improves the spatial resolution of fNIR, and reduces device costs.
  • the brain-computer interface device includes a light source, a time domain delay module, a wavelength-dependent optical splitting module, a sensor network, and a sensor front end; wherein the light source is used to provide a wide-spectrum pulse train, and the time-domain delay module is used to convert The pulsed optical train is converted into a multi-wave pulsed optical train.
  • the wavelength-dependent optical splitting module is used to decompose the multi-wave pulsed optical train into a sparse pulsed optical train.
  • the sensor network is used to send the sparse pulsed optical train to the sensing point of the sensing front end.
  • the sensing front end is used to send sparse pulsed light trains to the target brain through the sensing point to obtain sensing information, so that the detection light of different wavelengths is obtained by using wide-spectrum pulsed light and time-domain delay technology, without setting up multiple light sources, There is no need to increase the corresponding wavelength control module, so that the high spatial resolution of the brain-computer interface is realized on the basis of ensuring the miniaturization of the brain-computer interface.
  • the brain-computer interface device further includes a signal processing module, and the signal processing module is configured to convert sensing information into sensing data.
  • a signal processing module is also provided in the brain-computer interface device to process the sensing information collected by the sensing front end, which improves the feasibility of the solution.
  • the sensing information is a sensing light signal
  • the signal processing module includes a photoelectric detection unit, an analog-to-digital conversion unit, and a data processing unit;
  • the photoelectric detection unit is used to convert the sensing light signal into a The sensing signal;
  • the analog-to-digital conversion unit is used to convert the sensing electrical signal into a sensing digital signal;
  • the data processing unit is used to convert the sensing digital signal into sensing data.
  • the signal processing module includes a variety of processing units, which can convert sensing signals into sensing data that can be processed by other devices, which improves the feasibility of the solution.
  • the sensing front end is also used to acquire brainwave signals of the target brain
  • the analog-to-digital conversion unit includes a high-speed analog-to-digital conversion subunit and a low-speed analog-to-digital conversion subunit, and the high-speed conversion subunit It is used to convert the sensing electric signal into the first sensing digital signal
  • the low-speed analog-to-digital conversion subunit is used to convert the brain wave signal into the second sensing digital signal
  • the data processing unit is specifically used to convert the first sensing digital signal and converting the second sensing digital signal into sensing data.
  • the sensing front end not only provides sensing signals, but also provides brain wave signals, so as to provide two different modal signals, which improves the processing accuracy of sensing signals and the recognition of complex signal patterns. ability.
  • the sensing front end further includes an electrode unit, and the electrode unit is used to acquire brain wave signals of the target brain.
  • the sensing front end acquires brain wave signals through the electrode unit, which improves the feasibility of the solution.
  • the low-speed analog-to-digital conversion subunit is connected to the sensor network, and the material of the sensor network and the material of the sensor front end are conductive materials.
  • the sensor front-end directly acquires brain wave signals through the sensor network, which improves the miniaturization of the brain-computer interface device.
  • the wavelength-dependent optical splitting module includes an optical signal monitoring unit, and the optical signal monitoring unit is used to send the optical signal information of N sparse pulse optical trains to the signal processing module, and the signal processing module uses It is used to adjust the sensing detection light provided by the light source according to the light signal information.
  • a feedback mechanism is set for the light source, so that the filter characteristics of the wavelength-dependent optical splitting module can be adapted and the output power of the light source can be stabilized, which improves the detection accuracy of the brain-computer interface device.
  • the brain-computer interface device further includes a data transmission module, and the data transmission module is used to send the sensing data to the host computer.
  • a data transmission module is also set in the brain-computer interface device, and the data transmission module is a wireless communication module, which is used to send the sensing data to the host computer for the host computer to perform processing on the sensing data. Further processing improves the feasibility of the scheme.
  • the brain-computer interface device further includes an optical amplifier, and the optical amplifier is used to enhance the optical power of the wide-spectrum pulse train.
  • an optical amplifier is also provided in the brain-computer interface device to enhance the optical power of the wide-spectrum pulse train and improve the detection accuracy of the brain-computer interface device.
  • the sensing front end includes an optical fiber interface for receiving N sparse pulsed light trains, and the optical fiber interface is parallel to the irradiation directions of the N sparse pulsed light trains.
  • the optical fiber interface is parallel to the irradiation directions of the N sparse pulse light trains, and the layout structure is simple, which improves the structural and mechanical stability of the brain-computer interface device.
  • the sensing front end further includes a beam steering unit, and the beam steering unit is configured to change the irradiation direction of the N sparse pulse trains.
  • the irradiation directions of the optical fiber interface and the N sparse pulsed light trains are not parallel, which simplifies the integration of the sensing front end and the external structure of the brain-computer interface device, and simplifies the layout of the sensing network optical fiber.
  • the sensing front end includes a skin contact
  • the contact surface between the skin contact and the target brain is a spherical surface, a hemispherical surface or a smooth curved surface.
  • the contact surface between the skin contact and the target brain is a spherical, hemispherical or smooth curved surface, which enhances user experience.
  • the material of the skin contact is a flexible material.
  • the material of the skin contact is a flexible material, which further enhances user experience.
  • the second aspect of the present application provides an information acquisition method, the information acquisition method is applied to the brain-computer interface device in any possible implementation of the first aspect or the first aspect, the method includes: controlling the light source to provide a sensor The detection light, the sensing detection light includes a plurality of wide-spectrum pulse trains, the repetition frequency of the multiple broad-spectrum pulse trains is the first repetition frequency, and each broad-spectrum pulse train is composed of multiple pulse lights of different wavelengths; the control The time-domain delay module converts multiple wide-spectrum pulse trains into multiple multi-wave pulse trains, each multi-wave pulse train includes multiple pulse lights of different wavelengths, and the repetition frequency of multiple pulse lights of different wavelengths is the first Two repetition frequency, the second repetition frequency is N times of the first repetition frequency, N is the number of wavelength types of pulsed light with multiple different wavelengths; the wavelength-dependent optical splitting module is controlled to decompose multiple multi-wave pulse light trains into N sparse pulses Light trains, each sparse pulse light train includes multiple pulse lights of the same wavelength, the repetition frequency of multiple pulse lights
  • the brain-computer interface includes a light source, a time-domain delay module, a wavelength-dependent optical splitting module, a sensor network, and a sensor front end;
  • the light source is used to provide a wide-spectrum pulse train, and the time-domain delay module
  • the pulsed optical train is converted into a multi-wave pulsed optical train.
  • the wavelength-dependent optical splitting module is used to decompose the multi-wave pulsed optical train into a sparse pulsed optical train.
  • the sensor network is used to send the sparse pulsed optical train to the sensing point of the sensing front end.
  • the sensing front end is used to send sparse pulsed light trains to the target brain through the sensing point to obtain sensing information, so that the detection light of different wavelengths is obtained by using wide-spectrum pulsed light and time-domain delay technology, without setting up multiple light sources, There is no need to increase the corresponding wavelength control module, so that the high spatial resolution of the brain-computer interface is realized on the basis of ensuring the miniaturization of the brain-computer interface.
  • FIG. 1 is a schematic diagram of an embodiment of a brain-computer interface device provided by the embodiment of the present application
  • FIG. 2 is a schematic diagram of multiple broad-spectrum pulse trains provided by the embodiment of the present application.
  • FIG. 3 is a schematic diagram of multiple multi-wave pulse trains provided by the embodiment of the present application.
  • FIG. 4 is a schematic diagram of multiple sparse pulse trains provided by the embodiment of the present application.
  • Fig. 5 is a schematic diagram of another embodiment of a brain-computer interface device provided by the embodiment of the present application.
  • FIG. 6 is a schematic diagram of a sensing light signal provided by an embodiment of the present application.
  • Fig. 7 is a schematic diagram of another embodiment of a brain-computer interface device provided by the embodiment of the present application.
  • Fig. 8 is a schematic diagram of another embodiment of a brain-computer interface device provided by the embodiment of the present application.
  • Fig. 9 is a schematic diagram of another embodiment of a brain-computer interface device provided by the embodiment of the present application.
  • Fig. 10 is a schematic diagram of an embodiment of the sensing front-end structure provided by the embodiment of the present application.
  • Fig. 11 is a schematic diagram of another embodiment of the sensing front-end structure provided by the embodiment of the present application.
  • FIG. 12 is a schematic diagram of an embodiment of an information acquisition method provided by an embodiment of the present application.
  • the embodiment of the present application provides a brain-computer interface device, which is used to realize high spatial resolution of the brain-computer interface on the basis of ensuring the miniaturization and integration of the brain-computer interface.
  • the embodiment of the present application also provides a corresponding information acquisition method. Each will be described in detail below.
  • Brain-computer interface is the in-depth development of Human-Computer Interface (HCI). Traditional human-computer interaction technology needs to be realized with the help of media layer software and hardware, such as computer display screen, visual interface, mouse, etc.
  • the brain-computer interface realizes the understanding of brain consciousness through direct detection of brain activity, and through bioengineering methods, such as optogenetic methods, brain electrodes, etc., to achieve intervention and even participate in brain activities.
  • Non-invasive brain-computer interface refers to a brain-computer sensing method that installs brain signal sensing devices on the scalp and unexpected areas and avoids any surgical operations.
  • a typical non-invasive brain-computer structure, such as brain wave sensing collects brain waves through electrical methods, and obtains brain activity information by analyzing brain wave patterns.
  • NIR Near-infrared imaging
  • fNIR The functional infrared technology developed on this basis can detect the activity of neurons and is widely used in non-invasive brain-computer interfaces.
  • fNIR uses hemoglobin in the blood as a medium to obtain information on brain nerve activity. Specifically, the activity of human brain neurons requires oxygen consumption. Oxygen in the blood is carried by hemoglobin. Therefore, the higher the activity of the cerebral cortex, the greater the consumption of blood oxygen in this area, and the higher the concentration of hemoglobin (oxygenated hemoglobin HbO and deoxygenated hemoglobin HbR).
  • the concentration of hemoglobin determines the absorption rate of near-infrared light, that is, the ratio of incident and scattered NIR light power. Therefore, by detecting the incident NIR light power and the scattered light power passing through the brain tissue around the incident light, the activity level of the cortex in the local brain area can be analyzed.
  • the brain-computer interface device and the information acquisition method provided in the embodiments of the present application will be described in detail in combination with the above-mentioned explanations on the concepts of the brain-computer interface and fNIR.
  • an embodiment of a brain-computer interface device includes: a light source 100 , a time domain delay module 200 , a wavelength-dependent optical splitting module 300 , a sensor network 400 and a sensor front end 500 .
  • the light source 100 is used to provide sensing detection light, wherein the sensing detection light includes a plurality of broad-spectrum pulse trains, the repetition frequency of the multiple broad-spectrum pulse trains is the first repetition frequency, and each broad-spectrum pulse train Composed of multiple pulsed lights of different wavelengths;
  • the time domain delay module 200 is used to convert multiple wide-spectrum pulse trains into multiple multi-wave pulse trains, wherein each multi-wave pulse train includes multiple pulses of different wavelengths Light, the repetition frequency of multiple pulse lights of different wavelengths is the second repetition frequency, the second repetition frequency is N times the first repetition frequency, and N is the number of wavelength types of multiple pulse lights of different wavelengths;
  • the wavelength-dependent optical splitting module 300 It is used to decompose multiple multi-wave pulse light trains into N sparse pulse light trains, wherein each sparse pulse light train includes multiple pulse lights of the same wavelength, and the repetition frequency of multiple pulse lights of the same wavelength is the first repetition frequency
  • the sensor network 400 is used to send N sparse pulse light trains to the N sensing points
  • the light source 100 in the embodiment of the present application is a broad-spectrum pulsed light source, specifically a Kerr optical comb, a mode-locked laser or other broad-spectrum optical combs.
  • the sensing detection light provided by the light source 100 includes A plurality of broad-spectrum pulse trains, wherein the repetition frequency of the multiple broad-spectrum pulse trains is the first repetition frequency 1/T, that is, the time interval for each broad-spectrum pulse train generated by the light source 100 is T, and each Broad-spectrum pulse trains are composed of multiple pulsed lights of different wavelengths, that is, discrete N wavelength components, N is the number of wavelength components, and the adjacent intervals of different wavelengths are equal.
  • the time-domain delay module 200 in the embodiment of the present application can be an optical fiber delay line, a dispersion module or a dispersive waveguide, etc.
  • an optical fiber delay line with a specific length and a specific dispersion coefficient is used as the time-domain delay module 200 .
  • the sensing detection light generated by the light source 100 is transmitted to the time-domain delay module 200, and multiple wide-spectrum pulse trains pass through the time-domain delay module 200 to generate walk-off through dispersion, that is, optical signals of different wavelengths propagate at different speeds in the dispersive medium, so Optical signal walk-off occurs, forming time-staggered pulse light trains of different wavelengths, that is, forming multiple multi-wave pulse light trains, as shown in Figure 3, each multi-wave pulse light train includes multiple pulse lights of different wavelengths , the repetition frequency of a plurality of pulsed lights of different wavelengths is the second repetition frequency, and the second repetition frequency is N times the first repetition frequency, that is, the second repetition frequency is N/T, and the time domain delay module 200 blocks generate each different The time interval of the pulsed light with different wavelengths is T/N, where N is the number of wavelengths of multiple pulsed lights with different wavelengths, and the N kinds of wavelengths appear alternately in sequence.
  • the wavelength-dependent optical splitting module 300 in the embodiment of the present application is an optical splitter, specifically a wavelength division multiplexer (DEMUX), and the multiple multi-wave pulse trains generated by the time domain delay module 200 are transmitted to the wavelength-dependent optical splitting module 300, as shown in FIG. 4, the wavelength-dependent optical splitting module 300 decomposes multiple multi-wave pulse light trains into N sparse pulse light trains, wherein each sparse pulse light train includes multiple pulse lights of the same wavelength, and multiple The repetition frequency of the pulsed light of the same wavelength is the first repetition frequency 1/T, that is, the time interval of each pulsed light of the same wavelength generated by the wavelength-dependent optical splitting module 300 is T.
  • DEMUX wavelength division multiplexer
  • the sensor network 400 in the embodiment of the present application is a passive optical network (passive optical network, PON), and the N sparse pulse trains generated by the wavelength-dependent optical splitting module 300 are transmitted to the sensor network 400, and the sensor network There are N optical paths in 400.
  • the optical paths are composed of optical fibers, specifically printed polymer waveguides or other optical waveguides.
  • the sensing front end 500 includes N sensing points, and each branch of the sensing front end 500 is optically connected to a sensing point. At the sensing point of the sensing front end 500, the sensing network 400 sends N sparse pulse optical trains to the N sensing points of the sensing front end 500 through N optical paths, that is, the optical signals transmitted on each optical path are of the same wavelength.
  • the pulsed light is formed with a time interval of T.
  • the time intervals between the pulsed lights are sequentially different from each other by T/N.
  • the sensing front end 500 sends N sparse pulsed light trains to the target brain 600 through N sensing points, and the N sparse pulsed light trains pass through the skull and various layers of tissue of the target brain 600, and are scattered by the cerebral cortex to form scattered light.
  • the light carries the brain nerve activity level information in the brain area near the sensing point, that is, the sensing information, specifically the blood oxygen saturation intensity information, and the sensing front end 500 collects the sensing information to obtain the information of the target brain 600 .
  • the sensing point includes a light-emitting end and a light-receiving end, both of which are regarded as a single sensing point, and the light-emitting end and the light-receiving end are in one-to-one correspondence, that is, the sensing front end 500 includes 2N sensor points in total. Sensing points, where the light-emitting end is used to send sparse pulse light trains, and the light-receiving end is used to collect scattered light carrying sensing information.
  • the light source 100 , the time domain delay module 200 , the wavelength-dependent optical splitting module 300 , the sensor network 400 and the sensor front end 500 are all connected through optical fibers to conduct optical signals.
  • each wide-spectrum pulse train is composed of four discrete wavelength components
  • the second repetition frequency is 4/T
  • the time-domain delay module 200 generates pulsed light of each different wavelength
  • the time interval is T/4
  • the number of wavelength types of multiple pulsed lights with different wavelengths is 4
  • the wavelength-dependent optical splitting module 300 decomposes multiple multi-wave pulsed light trains into 4 sparse pulsed light trains
  • the sensor network 400 has 4 branches
  • the sensing front end 500 includes 4 sensing points.
  • the brain-computer interface includes a light source, a time-domain delay module, a wavelength-dependent optical splitting module, a sensor network, and a sensor front end;
  • the light source is used to provide a wide-spectrum pulse train, and the time-domain delay module
  • the pulsed optical train is converted into a multi-wave pulsed optical train.
  • the wavelength-dependent optical splitting module is used to decompose the multi-wave pulsed optical train into a sparse pulsed optical train.
  • the sensor network is used to send the sparse pulsed optical train to the sensing point of the sensing front end.
  • the sensing front end is used to send sparse pulsed light trains to the target brain through the sensing point to obtain sensing information, so that the detection light of different wavelengths is obtained by using wide-spectrum pulsed light and time-domain delay technology, without setting up multiple light sources, There is no need to increase the corresponding wavelength control module, so that the high spatial resolution of the brain-computer interface is realized on the basis of ensuring the miniaturization of the brain-computer interface.
  • another embodiment of a brain-computer interface device includes: a light source 100, a time domain delay module 200, a wavelength-dependent optical splitting module 300, a sensor network 400, a sensor front end 500 and a signal processing Module 700.
  • the signal processing module 700 includes a photoelectric detection unit 710 , an analog-to-digital conversion unit 720 and a data processing unit 730 , and the signal processing module 700 is used for converting sensing information into sensing data.
  • the sensing information is a sensing light signal
  • the photodetection unit 710 is used to convert the sensing light signal into a sensing electrical signal
  • the analog-to-digital conversion unit 720 is used to convert the sensing electrical signal into a sensing digital signal
  • the data processing unit 730 is used to convert the sensing digital signal into sensing data.
  • the light receiving end 520 of the sensing point collects the scattered light carrying the sensing information, that is, the sensing light signal, and then sends it to the photodetection unit 710 through the sensing network 400, where the wave division multiplexer and PON can be integrated into The PON (time and wavelength division multiplexed PON, TWDM-PON) system based on time division and wavelength division multiplexing, that is, the PON sending end 410, the PON sending end 410 is connected to N light emitting ends 510 through N optical paths, so as to realize point-to-multiple Point networking, the sensor network 400 and the wavelength division multiplexer (MUX) are integrated into a PON receiving end 420, and the PON receiving end 420 is connected to N optical receiving ends 520 through N optical paths, that is, the sensor network 400 includes 2N branches In the optical path, the MUX collects the sensing optical signals returned by N optical paths, and re-forms a wide-spectrum pulse train with a time interval of T/
  • each branch carries dynamic sensing information , so the pulse intensity of each pulse train is different.
  • the photodetection unit 710 is a photodiode (photo diode, PD), and the PD converts the wide-spectrum pulse light train into a sensing electrical signal.
  • the analog-to-digital conversion unit 720 is an analog-to-digital converter (analogue-to -digital conversion, ADC), the sampling rate of the ADC is N/T, and the sensing electrical signal is converted into a sensing digital signal at a sampling frequency of N/T.
  • ADC analog-to-digital converter
  • the data processing unit 730 converts the sensing digital signal into sensing data.
  • the data processing unit 730 is a digital signal processing unit (digital signal process, DSP), DSP analyzes the light intensity of each sensing point through the algorithm, and extracts the brain activity intensity at different space and time points by combining the prior spatial information of the sensing point and combining artificial intelligence systems and expert systems. , and abstract patterns of brain activity.
  • DSP digital signal processing unit
  • the brain-computer interface device also includes an optical amplifier, the optical amplifier is arranged between the time-domain delay module and the wavelength-dependent optical splitting module, the optical amplifier is used to enhance the optical power of the wide-spectrum pulse train, and the optical amplifier is a fiber amplifier or Semiconductor optical amplifiers, etc.
  • the PON sending end and the PON receiving end of the sensor network can be integrated and multiplexed into a transceiver 430 of a PON network, and any optical reciprocity Wavelength Division Multiplexer or Wavelength Division Multiplexer.
  • the light-emitting end and light-receiving end of the sensing front-end are also reconstructed into a structure that integrates transceivers, that is, each sensing point has the functions of a light-emitting end and a light-receiving end, that is, the sensor network 400 includes N
  • the sensing front end 500 includes N sensing points, wherein the PON transceiver 430 is connected to the N sensing points through N optical paths.
  • the wavelength-dependent optical splitting module 300 includes an optical signal monitoring unit 310, the optical signal monitoring unit 310 is used to send the optical signal information of N sparse pulse optical trains to the signal processing module 730, and the signal processing module 730 is used to transmit the optical signal information according to the optical signal information Adjust the sensing detection light provided by the light source 100 to form a feedback mechanism to match the filter characteristics of the wavelength-dependent optical splitting module 300 and stabilize the output power of the light source.
  • the brain-computer interface device also includes a data transmission module 900.
  • the data transmission module 900 is used to send the sensing data to the host computer.
  • the data transmission module 900 is a wireless communication module, and the wireless communication module is used to upload the data collected by the brain-computer interface device.
  • the original data, preprocessed data, status information, etc. of the computer are sent to the host computer, and at the same time, control signals, pre-trained models, equipment parameters, etc. are downloaded from the host computer.
  • the sensing front end 500 is also used to acquire brain wave signals of the target brain, and the analog-to-digital conversion unit 720 includes a high-speed analog-to-digital conversion subunit 721 and a low-speed analog-to-digital conversion subunit 721.
  • the conversion subunit 722 the high-speed conversion subunit 721 is used to convert the sensory electrical signal into the first sensory digital signal
  • the low-speed analog-to-digital conversion subunit 722 is used to convert the brain wave signal into the second sensory digital signal
  • data processing The unit 730 is specifically used to convert the first sensing digital signal and the second sensing digital signal into sensing data, so as to realize multi-modal signals, thereby improving the processing accuracy of signals, improving the ability to recognize complex signal patterns, etc. .
  • the first sensing digital signal and the second sensing digital signal multiplex a set of data processing unit 730, and the data processing unit 730 only regards signal inputs of different channels as signals of different modalities.
  • the data processing unit 730 includes independent or combined preprocessing modules for each modal signal.
  • the signal processing module 700 also includes a central processing unit 740, and the central processing unit 740 is used to: adjust the wavelength and wavelength interval of the light source 100; adjust the gain of the optical amplifier 800; adjust the spectral characteristics of the wavelength-dependent optical splitting module 300 and the spectral characteristics of the light source Matching; controlling the transimpedance amplifier mode of the photodetection unit 710; responsible for the synchronization of multi-modal signals; host computer information and data analysis; signal processing parameters and hyperparameter setting, calculation and configuration, etc.
  • the central processing unit 740 is used to: adjust the wavelength and wavelength interval of the light source 100; adjust the gain of the optical amplifier 800; adjust the spectral characteristics of the wavelength-dependent optical splitting module 300 and the spectral characteristics of the light source Matching; controlling the transimpedance amplifier mode of the photodetection unit 710; responsible for the synchronization of multi-modal signals; host computer information and data analysis; signal processing parameters and hyperparameter setting, calculation and configuration, etc.
  • the sensing front end 500 further includes an electrode unit 530 for acquiring brain wave signals of the target brain 600 .
  • the electrode unit 530 is connected to the low-speed analog-to-digital conversion subunit 722 through wires.
  • the low-speed analog-to-digital conversion subunit 722 is specifically an ADC array, each ADC corresponds to a wire, and each wire corresponds to an electrode unit 530.
  • Each electrode unit 530 is used to form an EEG channel to collect EEG signals, and the low-speed analog-to-digital conversion subunit 722 samples the collected analog signals, that is, EEG signals, into digital signals, that is, the second sensing digital signal.
  • the low-speed analog-to-digital conversion subunit 722 is connected to the sensor network 400. Specifically, it can be connected through wires.
  • the wires correspond to each optical path of the sensor network 400 one by one.
  • the material of 500 is a conductive material, that is, each optical path of the sensing network 400 and the sensing front end 500 are conductive.
  • conductive polymers are used to make the optical fibers of the sensing front end 500 and each optical path of the sensing network 400 or Optical fiber cladding.
  • the central processor 740 is integrated inside the signal processing module 700
  • the photodetection unit 710 is integrated outside the signal processing module 700 as a unit that needs to be adjusted by the central processor 740 .
  • the sensing front end includes an optical fiber interface 503, a beam spatial modulation unit 504, a skin contact 505, a sleeve 502, etc., and the optical fiber interface 503 is used to pass
  • the optical fiber 501 receives N sparse pulse light trains, and the contact surface between the skin contact 505 and the target brain is a spherical, hemispherical or smooth curved surface.
  • the material of the skin contact 505 is a flexible material, or a flexible conductive material.
  • the optical fiber 501 coincides with the direction of the sensing light, that is, the optical fiber interface 503 is parallel to the irradiation direction of the N sparse pulse light trains.
  • the optical fiber 501 does not coincide with the sensing direction.
  • the sensing front end also includes a beam steering unit 506.
  • the beam steering unit 506 is used to change the irradiation direction of N sparse pulse trains, such as optical fiber
  • the interface 503 is perpendicular to the irradiation direction of the N sparse pulse trains.
  • the brain-computer interface device further includes a skeleton as a support for the device.
  • the skeleton is a rigid skeleton or a flexible elastic wearable fabric as the skeleton.
  • an embodiment of an information acquisition method provided by this application includes:
  • the sensing detection light includes a plurality of broad-spectrum pulse trains, the repetition frequency of the multiple broad-spectrum pulse trains is the first repetition frequency, and each broad-spectrum pulse train is composed of multiple pulse lights of different wavelengths;
  • Control the time-domain delay module to convert multiple wide-spectrum pulse trains into multiple multi-wave pulse trains.
  • each multi-wave pulse light train includes a plurality of pulse lights of different wavelengths, the repetition frequency of the pulse lights of a plurality of different wavelengths is the second repetition frequency, and the second repetition frequency is N times the first repetition frequency, where N is multiple The number of wavelength types of pulsed light of different wavelengths;
  • Control the wavelength-dependent optical splitting module to decompose multiple multi-wavelength pulse trains into N sparse pulse trains.
  • each sparse pulse light train includes multiple pulse lights of the same wavelength, and the repetition frequency of the multiple pulse lights of the same wavelength is the first repetition frequency;
  • Control the sensing front end to send N sparse pulse light trains to the target brain through N sensing points, so as to obtain sensing information.
  • the execution body of the information acquisition method is the central processing unit in the brain-computer interface device.
  • the specific implementation of the information acquisition method provided in the embodiment of the present application reference may be made to the description of the brain-computer interface device in the foregoing embodiments, and details will not be repeated in the embodiments of the present application.
  • the light source is controlled to provide a wide-spectrum pulse train
  • the time-domain delay module is controlled to convert the wide-spectrum pulse train into a multi-wave pulse train
  • the wavelength-dependent optical splitting module is controlled to decompose the multi-wave pulse train into sparse pulses Optical array
  • control the sensor network to send sparse pulsed optical arrays to the sensing points of the sensing front end
  • control the sensing front end to send sparse pulsed optical arrays to the target brain through the sensing points, in order to obtain sensing information
  • wide spectrum Pulsed light and time domain delay technology obtain different wavelengths of probe light, without setting up multiple light sources, and without adding corresponding wavelength control modules, thus realizing the high space of the brain-computer interface on the basis of ensuring the small-scale integration of the brain-computer interface resolution.
  • the disclosed system, device and method can be implemented in other ways.
  • the device embodiments described above are only illustrative.
  • the division of the units is only a logical function division. In actual implementation, there may be other division methods.
  • multiple units or components can be combined or May be integrated into another system, or some features may be ignored, or not implemented.
  • the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be in electrical, mechanical or other forms.
  • the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.
  • each functional unit in each embodiment of the present application may be integrated into one processing unit, each unit may exist separately physically, or two or more units may be integrated into one unit.
  • the above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.
  • the integrated unit is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer-readable storage medium.
  • the technical solution of the present application is essentially or part of the contribution to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium , including several instructions to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in the various embodiments of the present application.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM, read-only memory), random access memory (RAM, random access memory), magnetic disk or optical disc, etc., which can store program codes. .

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Abstract

L'invention concerne un appareil d'interface cerveau-ordinateur et un procédé d'acquisition d'informations, qui se rapportent au domaine de l'Internet des objets. L'appareil d'interface cerveau-ordinateur comprend une source de lumière (100), un module de retard de domaine temporel (200), un module de division de lumière associé à la longueur d'onde (300), un réseau de détection (400) et une extrémité avant de détection (500), la source de lumière (100) étant utilisée pour fournir une séquence de lumière d'impulsion à large spectre ; le module de retard de domaine temporel (200) est utilisé pour convertir la séquence de lumière d'impulsion à large spectre en une séquence de lumière d'impulsion à ondes multiples ; le module de division de lumière associé à la longueur d'onde (300) est utilisé pour décomposer la séquence de lumière à impulsions multiples en une séquence de lumière à impulsions éparses ; le réseau de détection (400) est utilisé pour envoyer la séquence de lumière à impulsions éparses à des points de détection de l'extrémité avant de détection (500) ; et l'extrémité avant de détection (500) est utilisée pour envoyer la séquence de lumière à impulsions éparses à un cerveau cible (600) au moyen des points de détection, de façon à acquérir des informations de détection. Au moyen de l'appareil, une lumière de détection ayant différentes longueurs d'onde est obtenue à l'aide d'une technologie de retard de domaine temporel et de lumière d'impulsion à large spectre, et il n'est pas nécessaire de fournir une pluralité de sources de lumière (100), ni d'ajouter un module de commande de longueur d'onde correspondant, ce qui permet de réaliser la résolution spatiale élevée d'une interface cerveau-ordinateur sur la base de l'assurance de la miniaturisation et de l'intégration de l'interface cerveau-ordinateur.
PCT/CN2022/142182 2021-12-27 2022-12-27 Appareil d'interface cerveau-ordinateur et procédé d'acquisition d'informations Ceased WO2023125478A1 (fr)

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