WO2020054893A1 - Appareil et procédé de classification, sur la base d'un signal biologique, du niveau de douleur - Google Patents

Appareil et procédé de classification, sur la base d'un signal biologique, du niveau de douleur Download PDF

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WO2020054893A1
WO2020054893A1 PCT/KR2018/010854 KR2018010854W WO2020054893A1 WO 2020054893 A1 WO2020054893 A1 WO 2020054893A1 KR 2018010854 W KR2018010854 W KR 2018010854W WO 2020054893 A1 WO2020054893 A1 WO 2020054893A1
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signal
energy
pulse wave
zero crossing
electrocardiogram
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Korean (ko)
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유선국
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Industry Academic Cooperation Foundation of Yonsei University
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Industry Academic Cooperation Foundation of Yonsei University
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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
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • 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
    • A61B5/02—Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
    • A61B5/024—Measuring pulse rate or heart rate

Definitions

  • the present invention relates to a biosignal-based pain depth classification apparatus and method for classifying pain depth using an electrocardiogram (ECG), a photoplethysmograph (PPG) measurement device, and more specifically, pain from an ECG or PPG signal.
  • ECG electrocardiogram
  • PPG photoplethysmograph
  • It relates to a bio-signal-based pain depth classification apparatus and method capable of classifying pain depths with simple and high accuracy, by expressing the pain depth index through a sigmoid function.
  • the pain is divided into nociceptive pain, neurogenic pain, non-atrial pain or psychogenic pain.
  • somatic somatic pain
  • visceral pain visceral pain
  • central pain somatic pain
  • somatic pain is divided into surface pain and deep pain.
  • the depth of pain indicates that the pain occurs at a certain depth of a predetermined part of the body, that is, the pain is classified according to the occurrence region.
  • pain is highly subjective, so it is quite difficult to classify it.
  • the present invention relates to examination, diagnosis and risk stratification of clinical outbreaks such as acute coronary syndrome in patients with signs and symptoms of suspected heart disease causes will be.
  • the present invention detects ECG and, in addition, extracts a material stream (sample) of a patient's body fluid, etc., to obtain sample data using an in vitro diagnostic assay, and uses them to stratify diagnosis and risk.
  • an ECG without an ST segment shift or a T-wave change is regarded as “negative”, and an “positive” ECG refers to an ECG having an ST segment inhibition or increase of 2 mV or more, and is ambiguous.
  • ECGs that cannot be interpreted or interpreted eg, left-angle blockage, constant rhythm, extensive pathological Q-wave, and / or persistent ST segment increase after previous AMI measurements) are considered “negative”.
  • Korean Patent Publication No. 10-2006-0017510 analyzes the risk according to pain using an electrocardiogram, the depth of pain cannot be known only by analyzing the ST fragment and T-wave in the ECG parameters.
  • Korean Patent Registration No. 10-1000761 relates to medical equipment for measuring pain and consciousness level of surgical patients, and in particular, accurately measures and displays surgical pain / consciousness level of surgical patients with minimal error.
  • the present invention relates to an apparatus and method for measuring pain / consciousness of a surgical patient so as to prevent pain of the surgical patient.
  • the apparatus for measuring the pain / consciousness level of a surgical patient of the present invention detects an electrical potential of the stimulus signal at a second site of the surgical patient, and a stimulus signal generator for applying a stimulus signal to the first site of the surgical patient.
  • a bio-signal detection unit for amplifying and converting the detected electric potential to output a somatosensory-evoked electric potential test (SSEP) signal, a bio-signal conversion processing unit for converting and processing the SSEP signal to generate digital potential data, and the digital potential data in an index ( index) to generate and display pain / consciousness level information of the surgical patient.
  • SSEP somatosensory-evoked electric potential test
  • Korean Patent Registration No. 10-1000761 in order to know the degree of pain, stimulation is applied to a predetermined site, and a trigger potential generated according to the stimulation at another site is determined to determine pain according to the site.
  • a stimulus signal generator that directly applies stimuli
  • it is also necessary to locate the biosignal detector in a predetermined position which is dangerous, and can be used only by highly skilled personnel.
  • the technical problem to be solved by the present invention is from the ECG or PPG signal, when the sympathetic nervous system is excited by pain stimulation, energy, which is the main characteristic of the ECG signal or PPG signal according to blood flow and tachycardia reduction, and zero-crossing rate (Zero-crossing) rate) is extracted and normalized, and the value calculated by weighting the normalized energy and the zero crossing rate is a pain depth index through a sigmoid function. It is to provide a classification apparatus and method.
  • the pulse wave signal or the electrocardiogram signal detected from the pulse wave (PPG, light volume pulse wave) sensor unit or the electrocardiogram (ECG) sensor unit is converted to a digital signal through the A / D conversion unit and the calculation processing unit
  • the processing unit detects the pain depth index from the received pulse wave signal or the electrocardiogram signal. Zero-crossing rate) is detected and normalized, and a pain depth index is detected using a normalized energy and a sigmoid function of zero crossing rate.
  • the calculation processing unit detects and normalizes the energy and zero crossing ratio from the pulse wave signal or the electrocardiogram signal, obtains the sigmoid function of the energy and the sigmoid function of the zero crossing ratio, and multiplies the sigmoid function of energy by a preset energy weight.
  • the sum of the product of the zero cross rate multiplied by the sigmoid function of the predetermined zero cross rate is output as a pain depth index.
  • the operation processing unit filters the pulse wave signal or the electrocardiogram signal received from the A / D converter to remove noise, and in the filtered pulse wave signal or electrocardiogram signal, during a preset energy detection reference time period, the pulse wave signal or the electrocardiogram signal.
  • the energy of the pulse wave signal per reference hour or the electrocardiogram signal per reference hour is obtained by summing the squares of.
  • the calculation processing unit filters the pulse wave signal or the electrocardiogram signal received from the A / D converter to remove noise, and in the filtered pulse wave signal or electrocardiogram signal, the maximum value is the maximum, minimum, and maximum time values.
  • the point time, the minimum point time, which is the time at the minimum value, is detected, and the number of times the sign of the pulse wave signal or the electrocardiogram signal changes during the zero crossing reference time interval is determined as the zero crossing rate.
  • the zero-interval reference time interval is from the previous 15 seconds before the maximum point time to the maximum point time point.
  • the calculation processing unit normalizes the energy by dividing it into a standard normal distribution of energy, and normalizes it by dividing the zero crossing ratio by the standard normal distribution of the zero crossing rate.
  • the calculation processing unit performs filtering to remove noise from a pulse wave signal or an electrocardiogram signal received from the A / D converter during a standard normal distribution detection time period, at the initial stage of signal detection, and filtered
  • the square wave of the pulse wave signal or the electrocardiogram signal is summed to obtain the energy of the pulse wave signal per hour or the electrocardiogram signal per reference hour, and the obtained pulse wave signal per reference hour or the electrocardiogram per reference hour From the energies, the standard deviation and average are found to get the standard normal distribution of the energy.
  • the calculation processing unit performs filtering to remove noise from the pulse wave signal or the electrocardiogram signal received from the A / D converter during the standard normal distribution detection time interval, in the early stage of signal detection and filtering
  • the zero crossing rate which is the number of times the sign of the pulse wave signal or the electrocardiogram signal is changed during the zero crossing reference time interval, is obtained by obtaining the standard deviation and average to obtain a standard normal distribution of the zero crossing rate.
  • the calculation processing unit performs filtering to remove noise from the pulse wave signal or the electrocardiogram signal received from the A / D converter during the standard normal distribution detection time period, at the initial stage of signal detection, and from the filtered pulse wave signal or ECG signal, the standard deviation
  • the standard normal distribution of the pulse wave signal or the electrocardiogram signal is obtained by obtaining the mean and the average normal distribution of the pulse wave signal or the electrocardiogram signal, and the standard normal distribution of energy and the standard normal distribution of the zero crossing rate are used.
  • the pulse wave signal or the electrocardiogram signal detected from the pulse wave (PPG, light volume pulse wave) sensor unit or the electrocardiogram (ECG) sensor unit is converted into a digital signal through the A / D converter and transmitted to the computation processor, and is calculated.
  • the operation processor may generate energy and zero crossing rate (Zero-) from the pulse wave signal or the electrocardiogram signal. Crossing rate) is detected and normalized, and a pain depth index is detected using a sigmoid function of normalized energy and zero crossing rate.
  • the pulse wave signal or the electrocardiogram signal detected from the pulse wave (PPG, light volume pulse wave) sensor unit or the electrocardiogram (ECG) sensor unit is converted into a digital signal through the A / D converter and transmitted to the computation processor, and is calculated.
  • the processing unit filters the received pulse wave signal or the electrocardiogram signal using a reshape filter to remove noise, and detects the pain depth index from the filtered pulse wave signal or the electrocardiogram signal.
  • the operation processing unit calculates the energy of the pulse wave signal per reference hour or the electrocardiogram signal per reference hour by summing the squares of the filtered pulse wave signal or the electrocardiogram signal during the energy detection reference time period from the filtered pulse wave signal or the electrocardiogram signal.
  • Energy calculation step The operation processor detects the maximum value, the minimum value, and the maximum point time, which is the time at the maximum value, and the minimum point time, which is the time at the minimum value, from the filtered pulse wave signal or ECG signal, and based on the minimum point or the maximum point.
  • the calculation processing unit applies the normalized energy output from the normalization step and the normalized zero crossing ratio to the sigmoid function to obtain a sigmoid function of energy and a sigmoid function of zero crossing ratio, and the sigmoid of energy
  • the sum function is multiplied by the energy multiplied by the preset energy weight and the value obtained by multiplying the zero cross-rate sigmoid function by the pre-set zero cross-rate weight, and calculated as a pain depth index. Is done.
  • a reshape filter is a filter that allows frequencies between 0.5 Hz and 8 Hz to pass.
  • E is the normalized energy
  • Z is the normalized zero crossing ratio
  • ⁇ is the slope parameter
  • w 1 is the energy weight
  • w 2 is the zero crossing weight
  • the gradient parameter ⁇ is 1.5 to 1.8, and the sum of the energy weight w1 and the zero crossing factor weight w2 is 1.
  • the pain depth index has a value between 0 and 1.
  • the computer-readable recording medium in which a program for implementing a method of driving the pain depth classification device based on the bio-signal of the present invention is recorded with a computer.
  • the biosignal-based pain depth classification apparatus and method of the present invention when the sympathetic nervous system is excited by pain stimulation from the ECG or PPG signal, energy, zero (0), which is the main characteristic of the ECG signal or PPG signal according to a decrease in blood flow and tachycardia
  • energy, zero (0) which is the main characteristic of the ECG signal or PPG signal according to a decrease in blood flow and tachycardia
  • the present invention can be used even by a beginner, and there is no risk of applying stimuli.
  • FIG. 1 is a block diagram illustrating a schematic configuration of a biosignal-based pain depth classification device of the present invention.
  • FIG. 2 is a flow chart for explaining a pain depth classification process performed by the operation processing unit of FIG. 1.
  • the present invention relates to a light method for a pain depth classification device based on a bio-signal, wherein the signal detected by the pulse wave (PPG, light volume pulse wave) sensor unit or the electrocardiogram (ECG) sensor unit, the operation processing unit 200 is an electrocardiogram (ECG) signal Alternatively, filtering is performed to remove noise from the pulse wave signal, and energy and zero-crossing rates are extracted from the filtered electrocardiogram (ECG) signal or pulse wave signal, and normalized. The value computed by weighting the zero crossing rate is displayed by displaying the pain depth index through a sigmoid function.
  • PPG pulse wave
  • ECG electrocardiogram
  • the energy is normalized using the standard normal distribution of energy (Standard Gaussian Distribution), and the zero crossing rate is normalized using the standard normal distribution of the zero crossing rate.
  • a sigmoid function value is obtained using a slope parameter, an energy weight and a zero crossing ratio weight, and the obtained sigmoid function value is output as a pain depth value.
  • FIG. 1 is a block diagram illustrating a schematic configuration of a biosignal-based pain depth classification apparatus of the present invention, a biosignal detection unit 100, a biosignal preprocessing unit 150, an A / D conversion unit 180, and a computation processing unit ( 200), a display unit 210, a memory unit 220.
  • the bio-signal detection unit 100 includes a pulse wave (PPG) sensor unit 110 or an electrocardiogram (ECG) sensor unit to detect a pulse wave (optical volume pulse wave) or an electrocardiogram.
  • PPG pulse wave
  • ECG electrocardiogram
  • the pulse wave (PPG) sensor unit 110 includes a light emitting unit (not shown) and a light receiving unit (not shown), and irradiates light to a blood vessel (blood flow) from the light emitting unit (not shown), and a blood vessel (blood flow) from the light receiving unit ) Transmits or receives light reflected from blood vessels (blood flow) and converts it into electrical signals to output, and this output signal represents the light volume pulse wave of the blood vessel, so for convenience, these are referred to as pulse wave.
  • the light emitting unit may be formed of light emitting diodes (LEDs) of red light (wavelength: 650-750 nm) and infrared (ray) light (wavelength: 850-1000 nm), and emit red light or infrared light into blood vessels.
  • LEDs light emitting diodes
  • the light-receiving unit (not shown) is composed of a photo diode or a light-receiving sensor (light sensor), which receives or transmits light reflected through a blood vessel, that is, red light or infrared light, and outputs it as an electric signal.
  • the pulse wave (PPG) sensor unit 110 may be mounted on any part (finger, toe, ear ball, upper body, lower body, chest, hand, foot, etc.) where blood vessels of the human body exist. It is preferably mounted on a finger.
  • the electrocardiogram (ECG) sensor unit 120 includes an electrocardiogram electrode (not shown) and a reference electrode (or ground electrode) (not shown), and detects an electrocardiogram signal. In some cases, there may be two ECG electrodes.
  • the electrocardiogram (ECG) sensor unit 120 may be mounted on a wrist, ankle, chest, upper body, lower body, and the like.
  • the bio-signal pre-processing unit 150 performs pre-processing to remove and amplify noise from the electrocardiogram signal or pulse wave signal.
  • the pulse wave (PPG) signal preprocessing unit 160 amplifies the pulse wave signal detected by the pulse wave (PPG) sensor unit 110 and performs preprocessing to remove noise.
  • the electrocardiogram (ECG) signal preprocessing unit 170 amplifies the pulse wave signal detected by the electrocardiogram (ECG) sensor unit 120 and performs preprocessing to remove noise.
  • the A / D converter 180 converts the pulse wave signal from the pulse wave (PPG) signal preprocessor 160 into a digital signal, and converts the ECG signal from the electrocardiogram (ECG) signal preprocessor 170 into a digital signal. .
  • the calculation processing unit 200 performs filtering to remove noise from the electrocardiogram (ECG) signal or pulse wave signal, and the energy and zero-crossing rate from the filtered electrocardiogram (ECG) signal or pulse wave signal. ) Is extracted and normalized, and the value calculated by weighting the normalized energy and the zero crossing ratio is displayed by displaying the pain depth index through a sigmoid function.
  • the operation processing unit 200 receives a pulse wave (PPG) signal or an electrocardiogram (ECG) signal from the A / D converter 180 and digitally passes the received pulse wave (PPG) signal or an electrocardiogram (ECG) signal. Filtering is performed through a filter (HPF) and a digital low-pass filter (LPF), and energy and zero crossing ratios are obtained from the filtered pulse wave (PPG) signal or electrocardiogram (ECG) signal.
  • PPG pulse wave
  • ECG electrocardiogram
  • the calculation processing unit 200 sums the squares of the pulse wave (PPG) signal or the electrocardiogram (ECG) signal during a preset energy detection reference time interval from the filtered pulse wave (PPG) signal or the electrocardiogram (ECG) signal.
  • the energy of the pulse wave (PPG) signal per reference hour or the electrocardiogram (ECG) signal per reference hour is obtained (S120).
  • the calculation processing unit 200 may use a filtered pulse wave (PPG) signal or an electrocardiogram (ECG) signal to have a maximum value, a minimum value, and a maximum value, which is the time when the maximum value is obtained, and a minimum value, which is the time when the minimum value is obtained. Detects the point time, and during the zero crossing reference time interval based on the minimum or maximum point, the number of times the zero (0) is passed, that is, the number of times the sign of the pulse wave (PPG) signal or the electrocardiogram (ECG) signal changes. It is calculated as a cross rate.
  • the zero crossing reference time period may be a period from a time point that is a predetermined time (for example, 15 seconds) ahead of the point time point to a time point that is the maximum point time point.
  • the calculation processing unit 200 is normalized by dividing the energy into a standard normal distribution of energy (Standard Gaussian Distribution), and, in addition, in order to normalize the zero crossing rate, the calculation processing unit 200 is a standard normalization of zero crossing rate Distribution, normalized by dividing the zero crossing ratio.
  • the standard normal distribution of energy and the standard normal distribution of the zero crossing rate are values detected and stored at the beginning of signal detection.
  • the calculation processing unit 200 obtains a sigmoid function value using a normalized energy and a zero crossing ratio, a gradient parameter, an energy weight and a zero crossing ratio weight, and displays the obtained sigmoid function value as a pain depth value ( 210) and the memory unit 220.
  • the operation processing unit 200 may be a computer.
  • FIG. 2 is a flow chart for explaining a pain depth classification process performed by the operation processing unit of FIG. 1.
  • the operation processing unit 200 receives a pulse wave (PPG) signal or an electrocardiogram (ECG) signal from the A / D converter 180 (S110).
  • PPG pulse wave
  • ECG electrocardiogram
  • the pulse wave (PPG) signal or the electrocardiogram (ECG) signal received in the signal receiving step is filtered through a digital high-pass filter (HPF) and a digital low-pass filter (LPF). Reshape filtering is performed.
  • the cutoff frequency of the digital high pass filter (HPF) and the cutoff frequency of the digital high pass filter (HPF) are preset frequencies, and the cutoff frequency of the digital high pass filter (HPF) is the cutoff frequency of the digital high pass filter (HPF).
  • Smaller than The reshape filter consists of a digital high-pass filter (HPF) and a digital low-pass filter (LPF).
  • the cutoff frequency of the digital high-pass filter (HPF) is 0.5 Hz
  • the digital low-pass filter (LPF) may be a filter passing through 8 Hz, that is, 0.5 Hz to 8 Hz.
  • the filtering step (S120) in the pulse wave (PPG) signal or the electrocardiogram (ECG) signal, during the energy detection reference time interval, the square wave of the pulse wave (PPG) signal or the electrocardiogram (ECG) signal is summed and pulse wave per reference time The energy of the (PPG) signal or the electrocardiogram (ECG) signal per reference time is obtained (S120).
  • the energy detection reference time period is a time period that is set at the initial use or set at the factory by the user, and is a time period for obtaining energy in the energy calculation step, and this time period is a time period for each energy. Because of this change, it is called a sliding window. That is, the energy detection reference time interval refers to a sliding window having a predetermined time interval based on the received time of the pulse wave (PPG) signal or the electrocardiogram (ECG) signal in the signal reception step. Get energy from the moving window.
  • the energy detection reference time can be 10 second intervals. That is, in this case, in the energy calculation step, it is possible to obtain energy from a time point of the current signal to a time point of the past 10 seconds from the time point of the current signal.
  • the maximum and minimum values of the pulse wave (PPG) signal or the electrocardiogram (ECG) signal, the maximum point time, which is the time when the maximum value, and the minimum point time, which is the time when the minimum value It detects and obtains the number of times that zero (0) passes, that is, the number of times that the sign of the pulse wave (PPG) signal or the electrocardiogram (ECG) signal changes during the zero crossing reference time interval based on the minimum or maximum point.
  • the waveform of the pulse wave (PPG) signal or the electrocardiogram (ECG) signals has hills and valleys, and the peak point in the portion representing the hill is called the maximum point, and the minimum portion in the portion representing the valley is the minimum point. Then, the amplitude value of the maximum point is called the maximum value, the amplitude value of the minimum point is called the minimum value, the time at the maximum value is called the maximum point time, and the time at the minimum value is called the minimum point time.
  • the zero crossing reference time interval is a time interval for obtaining the zero crossing rate in the zero crossing rate calculation step, and this time interval is referred to as a sliding window because the time interval changes with every zero crossing rate. That is, the zero crossing reference time period is based on the minimum point time, for a certain period of time, from the minimum point time to the maximum point time, or from the point where the maximum point time has passed a predetermined time to the maximum point time point. It can be set to a period of time, or from a time point that is a predetermined time in front of the maximum point time to a time point that is a predetermined time behind the maximum point time.
  • the zero crossing reference time period may be a period from a time point that is a predetermined time (for example, 15 seconds) in front of the maximum point time to a maximum point time point.
  • the reference time of energy detection and the reference time of zero crossing can be extended up to 5 minutes through a sliding window in consideration of the heart rate variation section.
  • the normalization step for the energy obtained in the energy calculation step, the standard normal distribution of energy is divided and normalized by dividing the energy obtained in the energy calculation step, and for the zero crossing rate obtained in the zero crossing rate calculation step, the standard normal distribution of the zero crossing rate By dividing the zero crossing rate obtained in the zero crossing rate calculation step, normalization is performed (S160).
  • the standard normal distribution of the energy and the standard normal distribution of the zero crossing rate are obtained during the standard normal distribution detection time interval at an initial stage in which signal detection is started using the biosignal-based pain depth classification device 10.
  • the standard normal distribution can be expressed as (X- ⁇ ) / ⁇ .
  • X is an energy signal or a zero crossing rate signal
  • ⁇ is a standard deviation of the energy or zero crossing rate
  • ⁇ is the average of the energy or zero crossing rate.
  • the standard normal distribution detection time interval is for obtaining a standard normal distribution of energy and a standard normal distribution of zero crossing for a period of time from an initial time point at which signal detection is started using the biosignal-based pain depth classification device 10.
  • time for example, it may be from a time point when a first pulse wave (PPG) signal or an electrocardiogram (ECG) signal is received to a time point in which 10 seconds to 2 minutes have elapsed.
  • PPG pulse wave
  • ECG electrocardiogram
  • the standard normal distribution detection time interval can be adjusted in consideration of the energy detection reference time, zero crossing reference time, and heart rate variation interval.
  • the calculation processing unit 200 is A
  • the / D converter 180 receives the received pulse wave (PPG) signal or the electrocardiogram (ECG) signal through the digital high-pass filter (HPF) and the digital low-pass filter (LPF) to reshape filtering.
  • the square of the pulse wave (PPG) signal or the electrocardiogram (ECG) signal is added up and the pulse wave per reference hour (PPG) signal or the electrocardiogram per reference hour ( ECG)
  • PPG pulse wave per reference hour
  • ECG electrocardiogram per reference hour
  • the number of times that zero (0) is passed that is, the number of times the sign of the pulse wave (PPG) signal or the electrocardiogram (ECG) signal is changed.
  • the standard normal distribution of energy and the standard normal distribution of the zero crossing rate first, during the detection period of the standard normal distribution, the pulse wave (PPG) signal or the electrocardiogram (ECG) signal, the calculation processing unit 200 Is received from the A / D converter 180, and performs reshape filtering on the received pulse wave (PPG) signal or electrocardiogram (ECG) signal through a digital high pass filter (HPF) and a digital low pass filter (LPF), From the filtered pulse wave (PPG) signal or the electrocardiogram (ECG) signal, the standard deviation and average are obtained to obtain the standard normal distribution of the pulse wave (PPG) signal or the electrocardiogram (ECG) signal, which is the standard normal distribution of energy and the standard of zero crossing rate. It can also be used instead of the normal distribution.
  • HPF digital high pass filter
  • LPF digital low pass filter
  • a sigmoid function value is obtained by using a slope parameter, an energy weight, and a zero cross rate weight for the normalized energy (E) and the zero cross rate in the normalization step (S170).
  • the sigmoid function refers to a function having a sigmoid curve (S), and is also a special form of a logistic function. It is a function mainly representing a learning curve, etc. It is a function that approaches a constant finite value from a small value close to 0.
  • the normalized energy (E) and the normalized zero crossing rate (Z) are multiplied by the slope parameter ( ⁇ ), respectively, and the energy weight (w 1 ) and the zero crossing rate weight (w 2 ) are used to make the two.
  • the sigmoid function w 1 ⁇ f (E) + w 2 ⁇ f (Z) is shown for the addition.
  • the sigmoid function of normalized energy (E) with energy weight (w 1 ) and gradient parameter ( ⁇ ), and normalized zero with zero crossing factor weight (w 2 ) and gradient parameter ( ⁇ ) It can be obtained by adding a sigmoid function of the crossing rate (Z), that is, w 1 / (1 + exp (- ⁇ E)) + w 2 / (1 + exp (- ⁇ Z)).
  • the energy weight, the zero cross ratio weight, and the slope parameter may be values set at the time of factory shipment or initial use.
  • the slope parameter ⁇ may be 1.5 to 1.8, and the sum of the energy weight w1 and the zero crossing factor weight w2 should be 1.
  • the sigmoid function value has a value between 0 and 1, where 0 means maximum pain, and 1 means no pain. In addition, by calculating an inverse, if 0 is no pain, if 1, pain can be expressed as the maximum.
  • the normalized energy and the normalized zero crossing ratio in the pain situation are lower than in the normal situation, and thus mapped to a low value in the sigmoid function to 0
  • the pain is high at a near level.
  • the sigmoid function has a value between 0 and 1
  • inverse calculation with 1-w 1 / (1 + exp (-E)) + w 2 / (1 + exp (-Z)) returns 1
  • a close figure may indicate a high level of pain.
  • the obtained sigmoid function value is output as a pain level (S180).
  • the expression w 1 ⁇ f (E) + w 2 ⁇ f (Z) in the sigmoid function mapping step may be referred to as a pain depth formula.
  • the present invention has a smoothing effect because it is strong in noise, simple in calculation, and squared and added at the time of energy detection.
  • the apparatus and method for classifying a pain depth based on a biosignal of the present invention can be classified as a simple and high-accuracy pain depth, and can be used as a device for diagnosing pain in general medical fields such as rehabilitation medicine.

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  • Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)

Abstract

La présente invention concerne un appareil de classification, sur la base d'un signal biologique, du niveau de douleur et un procédé de classification d'un niveau de douleur utilisant des dispositifs d'électrocardiographie (ECG) et de photopléthysmographie (PPG) et, plus spécifiquement, un appareil de classification, sur la base d'un signal biologique, du niveau de douleur et un procédé d'extraction, à partir d'un signal ECG ou PPG, de l'énergie et du taux de passage par zéro, qui sont les caractéristiques principales du signal ECG ou PPG, en fonction d'une diminution du débit sanguin et de la fréquence de pouls lorsque le système nerveux sympathique est excité en raison d'un stimulus douloureux. Ensuite l'énergie et le taux de passage par zéro extraits sont normalisés et un indice de niveau de douleur est affiché par l'intermédiaire d'une fonction sigmoïde à partir d'une valeur calculée par pondération de l'énergie et du taux de passage par zéro normalisés, ce qui permet une classification simple et hautement précise du niveau de douleur. La présente invention concerne un appareil de classification, sur la base d'un signal biologique, du niveau de douleur, dans lequel une onde de pouls (PPG) ou un signal ECG détecté par un capteur PPG ou un capteur ECG est converti en un signal numérique par une unité de conversion analogique/numérique de façon à être transmis à une unité de traitement informatique, qui détecte un indice de niveau de douleur à partir du signal PPG ou ECG reçu, l'unité de traitement informatique détectant l'énergie et un taux de passage par zéro à partir du signal PPG ou ECG et les normalisant, obtenant une fonction sigmoïde de l'énergie et une fonction sigmoïde du taux de passage par zéro, et ajoutant une valeur obtenue en multipliant la fonction sigmoïde de l'énergie par un poids prédéfini pour l'énergie et une valeur obtenue en multipliant la fonction sigmoïde du taux de passage par zéro par un poids prédéfini pour le taux de passage par zéro, ce qui permet de délivrer le résultat de l'addition en tant qu'indice de niveau de douleur.
PCT/KR2018/010854 2018-09-14 2018-09-14 Appareil et procédé de classification, sur la base d'un signal biologique, du niveau de douleur Ceased WO2020054893A1 (fr)

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