CN109965870B - Method for automatically detecting and stimulating treatment of epilepsy - Google Patents

Method for automatically detecting and stimulating treatment of epilepsy Download PDF

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CN109965870B
CN109965870B CN201910145631.5A CN201910145631A CN109965870B CN 109965870 B CN109965870 B CN 109965870B CN 201910145631 A CN201910145631 A CN 201910145631A CN 109965870 B CN109965870 B CN 109965870B
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CN109965870A (en
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万文妮
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Hangzhou Nuowei Medical Technology 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
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • 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
    • A61B5/369—Electroencephalography [EEG]
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/40—Detecting, measuring or recording for evaluating the nervous system
    • A61B5/4076—Diagnosing or monitoring particular conditions of the nervous system
    • A61B5/4094—Diagnosing or monitoring seizure diseases, e.g. epilepsy
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00—Electrotherapy; Circuits therefor
    • A61N1/18—Applying electric currents by contact electrodes
    • A61N1/32—Applying electric currents by contact electrodes alternating or intermittent currents
    • A61N1/36—Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
    • A61N1/3605—Implantable neurostimulators for stimulating central or peripheral nerve system
    • A61N1/3606—Implantable neurostimulators for stimulating central or peripheral nerve system adapted for a particular treatment
    • A61N1/36064—Epilepsy
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00—Electrotherapy; Circuits therefor
    • A61N1/18—Applying electric currents by contact electrodes
    • A61N1/32—Applying electric currents by contact electrodes alternating or intermittent currents
    • A61N1/36—Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
    • A61N1/3605—Implantable neurostimulators for stimulating central or peripheral nerve system
    • A61N1/36125—Details of circuitry or electric components
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00—Electrotherapy; Circuits therefor
    • A61N1/18—Applying electric currents by contact electrodes
    • A61N1/32—Applying electric currents by contact electrodes alternating or intermittent currents
    • A61N1/36—Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
    • A61N1/3605—Implantable neurostimulators for stimulating central or peripheral nerve system
    • A61N1/36128—Control systems
    • A61N1/36135—Control systems using physiological parameters

Abstract

The invention discloses a method for automatically detecting and stimulating epilepsy treatment, which comprises a detection scheme and a stimulation scheme, wherein the method for setting the detection scheme comprises the following steps: a chip in the doctor program controller samples brain waves of a patient in real time through an electrode and displays the brain waves in a time-amplitude curve graph; calculating the line length or area or half-wave slope of the brain wave curve graph by a preset detection algorithm; comparing the calculation result with a preset threshold value, and judging whether the patient suffers from epilepsy; the method of setting the stimulation protocol was as follows: the doctor program controller is connected with the nerve stimulator to control and send out a single stimulation command, and the adaptability of the patient to the parameters of the pulse train sent out by the nerve stimulator is detected; adjusting the number of pulse trains and parameters in the set stimulation waveform; after the detection scheme and the stimulation scheme are set, the nerve stimulator enters a self-response treatment state. The invention solves the technical problem that the existing nerve stimulator can not send out stimulation treatment according to the actual situation of an epileptic.

Description

Method for automatically detecting and stimulating treatment of epilepsy
Technical Field
The invention relates to the field of medical treatment, in particular to a method for automatically detecting and stimulating epilepsy treatment.
Background
Epilepsy is a chronic disease caused by abnormal discharges resulting from highly synchronized activity of neurons, causing convulsions or spasms, confusion, and sometimes even loss of consciousness, and is the second most common disease in the neurology department, second only to headache. Neuromodulation is a common surgical procedure for drug refractory epilepsy, including Vagal Nerve Stimulation (VNS), cortical electrical stimulation, and Deep Brain Stimulation (DBS). Most of the active implanted nerve stimulators for treating epilepsy on the market do not have the function of epilepsy detection, and only intermittently send out electrical stimulation for treatment. In the research on epilepsy detection, either offline data processing is performed on the acquired multi-channel electroencephalogram data and the moment of occurrence of epilepsy is judged, or online detection is performed on the basis of non-invasive wearable equipment and equipment with strong computing capability. The size and temperature rise requirements of the implanted device make the power consumption of the product not too large, and meanwhile, too complex algorithm is difficult to apply to the implanted device.
Disclosure of Invention
In order to solve the technical problem that the existing nerve stimulator cannot deliver stimulation treatment according to the actual condition of an epileptic patient, the invention provides a method for automatically detecting and stimulating to treat epilepsy.
The invention adopts the following technical scheme:
a method for automatically detecting and stimulating to treat epilepsy comprises a detection scheme and a stimulation scheme, wherein the detection scheme is set by the following method: a chip in the doctor program controller samples the brain waves of the patient through the electrodes, and the sampled data of the brain waves of the patient are transmitted to the doctor program controller through the wireless communication equipment and are displayed in a time-amplitude curve graph form; the doctor program controller calculates a brain wave curve graph according to a preset detection algorithm, and the detection algorithm calculates the line length or the area or the half-wave slope of the brain wave of the patient; comparing the size relationship between the calculation result of the line length or area or half-wave slope of the brain wave of the patient and a preset threshold value to judge whether the patient suffers from epilepsy;
the method of setting the stimulation protocol is as follows: the doctor program control instrument is connected with the nerve stimulator; controlling a nerve stimulator to send a single stimulation command by a doctor program controller, and detecting the adaptability of a patient to pulse train parameters sent by the nerve stimulator, wherein the pulse train parameters comprise current, frequency, pulse width and duration; setting the number of bursts and parameters in the stimulation waveform according to the patient's adaptation to the burst parameters;
after the detection scheme and the stimulation scheme are set, the neural stimulator enters a self-response treatment state.
Preferably, the operation steps of the nerve stimulator in the self-response state are as follows:
1. in the brain wave sampling process of a patient, the neural stimulator is determined by amplitude detection written into chip hardware by default
When the amplitude exceeds the set amplitude in the chip hardware, waking up the MCU to detect according to a preset detection scheme;
2. if the detection scheme detects that any one of the length, the area and the half-wave slope of the brain wave of the patient exceeds the preset value
The doctor program controller controls the nerve stimulator to respond to stimulation treatment according to the stimulation scheme;
3. when the detection scheme does not detect that any one of the length, the area and the half-wave slope of the brain wave of the patient exceeds a preset threshold and the abnormality does not occur for more than 5 minutes, the neural stimulator automatically enters a low power consumption mode of amplitude detection and is awakened when the amplitude is abnormal next time.
Preferably, the neurostimulator is an active implantable neurostimulator.
Preferably, the neurostimulator delivers a stimulation waveform comprising 1-6 pulse trains, each pulse train parameter being adjustable for current, frequency, pulse width and duration.
Preferably, the method for calculating whether the patient has epilepsy according to the brain wave length comprises the following steps:
1. presetting brain wave line length threshold on doctor program control instrument
Figure DEST_PATH_IMAGE002
Calculating the average line length of brain wave in a certain short time period t before the detection point
Figure DEST_PATH_IMAGE004
Wherein
Figure DEST_PATH_IMAGE006
；
2. Calculating the average line length of brain waves in a certain long time period T before the detection point
Figure DEST_PATH_IMAGE008
Wherein
Figure DEST_PATH_IMAGE010
；
3. Calculating the brain wave line length detection result
Figure DEST_PATH_IMAGE012
Wherein
Figure DEST_PATH_IMAGE014
；
4. Judging whether the brain wave line length detection result exceeds a threshold value
Figure 383419DEST_PATH_IMAGE002
When the threshold value is exceeded
Figure 834648DEST_PATH_IMAGE002
At that time, the marker is judged to be epileptic.
Preferably, the method for calculating whether the patient has epilepsy according to the brain wave area comprises the following steps:
1. calculating the average area in a certain short time period t before the detection point
Figure DEST_PATH_IMAGE016
Wherein
Figure DEST_PATH_IMAGE018
，
Brain wave voltage average value of middle patient
Figure DEST_PATH_IMAGE020
；
2. Calculating the average area in a certain long time period T before the detection point
Figure DEST_PATH_IMAGE022
Wherein
Figure DEST_PATH_IMAGE024
；
3. Calculating area detection results
Figure DEST_PATH_IMAGE026
Wherein
Figure DEST_PATH_IMAGE028
；
4. Judging whether the line length detection result exceeds a threshold value
Figure DEST_PATH_IMAGE030
When the threshold value is exceeded
Figure 749471DEST_PATH_IMAGE030
At that time, the marker is judged to be epileptic.
Preferably, the method for calculating whether the patient has epilepsy according to the slope of the half wave of the brain wave is as follows:
1. determining a given time period, sampling the brain waves of the patient in the time period to obtain a curve graph, and dividing each peak value and adjacent peak-valley in the curve graph as a half-wave;
2. calculating the duration of each half-wave
Figure DEST_PATH_IMAGE032
，
Figure DEST_PATH_IMAGE034
I.e. the frequency corresponding to the half-wave;
3. calculating the amplitude of each half-wave
Figure DEST_PATH_IMAGE036
；
4. Calculating the slope of each half-wave
Figure DEST_PATH_IMAGE038
；
5. Judging whether the slope calculation result of the half-wave exceeds the threshold value
Figure DEST_PATH_IMAGE040
When there is a slope exceeding the threshold
Figure 36358DEST_PATH_IMAGE040
And (4) judging that the patient suffers from epilepsy.
Preferably, the
Figure DEST_PATH_IMAGE042
Is the voltage value of the brain wave of the patient.
The invention has the beneficial effects that: 1. the amplitude detection and epilepsy treatment functions are added into the implantable neural stimulator, the neural stimulator is in a low power consumption mode of amplitude detection under the default condition, when the amplitude of a patient is abnormal, the neural stimulator restarts to wake up an MCU (microprogrammed control unit), the brain wave of the patient is detected according to a preset detection scheme, and the low energy consumption of the neural stimulator can meet the requirements of an implantable product; 2. the invention calculates the data sampled by the patient in real time according to the doctor program controller to judge whether the epilepsy occurs, and determines whether to trigger the electrical stimulation treatment according to the judgment result, thereby having high response speed and high accuracy.
Drawings
FIG. 1 is a schematic flow diagram of the detection scheme of the present invention;
FIG. 2 is a schematic flow diagram of a stimulation protocol of the present invention;
fig. 3 is a flow chart of the operation of the neurostimulator in the self-response state of the invention.
Detailed Description
The technical scheme of the invention is further described in detail by the following specific embodiments in combination with the attached drawings:
example (b): referring to fig. 1-3, a method for automatically detecting and stimulating epilepsy therapy includes setting a detection scheme and a stimulation scheme, wherein the detection scheme is set by the following method:
s101, sampling brain waves of a patient through a chip in a doctor program controller by virtue of an electrode, transmitting sampling data of the brain waves of the patient to the doctor program controller by virtue of wireless communication equipment, and displaying the sampling data in a time-amplitude curve graph;
s102, calculating a brain wave curve graph by a doctor program controller according to a preset detection algorithm, wherein the detection algorithm calculates the line length or the area or the half-wave slope of the brain wave of the patient;
s103, comparing the size relation between the calculation result of the line length or area or half-wave slope of the brain wave of the patient and a preset threshold value to judge whether the patient suffers from epilepsy.
The method of setting the stimulation protocol is as follows:
s201, connecting a doctor program control instrument with a nerve stimulator;
s202, controlling a nerve stimulator to send a single stimulation command by a doctor program controller, and detecting the adaptability of a patient to pulse train parameters sent by the nerve stimulator, wherein the pulse train parameters comprise current, frequency, pulse width and duration;
s203, setting the number of pulse trains in the stimulation waveform and parameters according to the adaptability adjustment of the patient to the pulse train parameters.
After the detection scheme and the stimulation scheme are set, the neural stimulator enters a self-response treatment state.
The operation steps of the nerve stimulator in the self-response state are as follows:
s301, in the brain wave sampling process of the patient, the neural stimulator defaults to judge by amplitude detection written in chip hardware
Otherwise, the neural stimulator is in a low-power-consumption operation state, and when the amplitude is detected to exceed the set amplitude in the chip hardware, the MCU is awakened to perform detection according to a preset detection scheme;
s302, if the detection scheme detects that any one of the length, the area and the half-wave slope of the brain wave of the patient exceeds the preset value
Setting a threshold value, and controlling the nerve stimulator to respond to stimulation treatment by the doctor program controller according to the stimulation scheme;
and S303, when the detection scheme does not detect that any one of the length, the area and the half-wave slope of the brain wave of the patient exceeds a preset threshold and the abnormality does not occur for more than 5 minutes, the neural stimulator automatically enters a low power consumption mode of amplitude detection and is awakened when the amplitude is abnormal next time.
The neurostimulator is an active implanted neurostimulator, a stimulation waveform sent by the neurostimulator comprises 1-6 pulse trains, parameters of each pulse train can adjust current, frequency, pulse width and duration, 4 types of biphasic symmetrical square wave pulse trains with different currents, frequencies, pulse widths and durations can be set in each stimulation scheme at most, the number of the pulse trains of one stimulation waveform is 1-6, and each pulse train can be selected from the 4 types of biphasic symmetrical square wave pulse trains so as to adapt to different degrees of illness of epileptics.
The chip in the doctor program-controlled instrument collects brain waves of a patient through an electrode, the chip is preset with an amplitude threshold value, the amplitude threshold value is adjustable, the chip transmits brain wave data of the patient to the doctor program-controlled instrument through wireless communication equipment and displays the brain wave data in a time-amplitude curve graph mode, synchronously, in the sampling process of the brain waves, the chip judges the amplitude of the brain waves of the patient in real time, when the brain wave amplitude of the patient exceeds the preset amplitude threshold value, the chip wakes up and activates a Micro Control Unit (MCU), the doctor program-controlled instrument calculates the length or area or half-wave slope of the brain waves according to a preset detection algorithm, and when the calculation result of any item exceeds the preset threshold value, the doctor program-controlled instrument sends a stimulation instruction to a nerve stimulator through the MCU.
The method for calculating whether the patient has epilepsy or not by the brain wave length comprises the following steps:
1. presetting brain wave line length threshold on doctor program control instrument
Figure 647468DEST_PATH_IMAGE002
Calculating the average line length of brain wave in a certain short time period t before the detection point
Figure 548559DEST_PATH_IMAGE004
Wherein
Figure 81172DEST_PATH_IMAGE006
；
2. Calculating the average line length of brain waves in a certain long time period T before the detection point
Figure 171750DEST_PATH_IMAGE008
Wherein
Figure 371787DEST_PATH_IMAGE010
；
4. Calculating the brain wave line length detection result
Figure 630730DEST_PATH_IMAGE012
Wherein
Figure 650638DEST_PATH_IMAGE014
；
5. Judging whether the brain wave line length detection result exceeds a threshold value
Figure 918809DEST_PATH_IMAGE002
When the threshold value is exceeded
Figure 707773DEST_PATH_IMAGE002
At that time, the marker is judged to be epileptic.
The linear length algorithm is to obtain the calculation result of the brain wave linear length by calculating the mean value ratio of the coastline of the time window of the period and the long time window.
The method for calculating whether the patient has the epilepsy or not by the brain wave area comprises the following steps:
1. calculating the average area in a certain short time period t before the detection point
Figure 355528DEST_PATH_IMAGE016
Wherein
Figure 862733DEST_PATH_IMAGE018
，
Brain wave voltage average value of middle patient
Figure 200173DEST_PATH_IMAGE020
；
4、Calculating the average area in a certain long time period T before the detection point
Figure 640382DEST_PATH_IMAGE022
Wherein
Figure 742592DEST_PATH_IMAGE024
；
5. Calculating area detection results
Figure 2672DEST_PATH_IMAGE026
Wherein
Figure 878225DEST_PATH_IMAGE028
；
4. Judging whether the line length detection result exceeds a threshold value
Figure 641781DEST_PATH_IMAGE030
When the threshold value is exceeded
Figure 944587DEST_PATH_IMAGE030
At that time, the marker is judged to be epileptic.
The area algorithm is to calculate the average value of the brain wave voltage amplitude, and then calculate the average ratio of the areas between the waveform and the average line of the short time window and the long time window.
The method for calculating whether the patient has epilepsy or not by using the slope of the half wave of the brain wave comprises the following steps:
1. determining a given time period, sampling the brain waves of the patient in the time period to obtain a curve graph, and dividing each peak value and adjacent peak-valley in the curve graph as a half-wave;
2. calculating the duration of each half-wave
Figure 160804DEST_PATH_IMAGE032
，
Figure 371206DEST_PATH_IMAGE034
I.e. the frequency corresponding to the half-wave;
3. calculating the amplitude of each half-wave
Figure 756313DEST_PATH_IMAGE036
；
4. Calculating the slope of each half-wave
Figure 230020DEST_PATH_IMAGE038
；
5. Judging whether the slope calculation result of the half-wave exceeds the threshold value
Figure 933533DEST_PATH_IMAGE040
When there is a slope exceeding the threshold
Figure 362940DEST_PATH_IMAGE040
And (4) judging that the patient suffers from epilepsy.
The half-wave slope algorithm calculates an extreme value in a time window, and takes the slope of a half-wave as a judgment index for judging whether the half-wave slope is abnormal or not.
In the calculation formula of line length and area, wherein
Figure 101088DEST_PATH_IMAGE042
Is the voltage value of the brain wave of the patient. When a detection algorithm is preset, one of three parameters of the line length, the area and the half-wave slope of brain waves can be taken as a judgment standard, different threshold values are respectively set for the three parameters of the line length, the area and the half-wave slope, when the parameter taken as the judgment standard exceeds the set threshold value, the patient is judged to be epileptic, multiple parameters can be selected for combined judgment, a coefficient is set for each parameter, and the setting of the coefficient can be obtained by experience or experiment.
The above-described embodiments are only preferred embodiments of the present invention, and are not intended to limit the present invention in any way, and other variations and modifications may be made without departing from the spirit of the invention as set forth in the claims.

Claims (6)

1. A system for automatically detecting and stimulating the treatment of epilepsy, comprising: the detection system comprises a doctor program-controlled instrument, electrodes and wireless communication equipment, the electrodes sample the brain waves of the patient, and the sampling data of the brain waves of the patient are transmitted to the doctor program-controlled instrument through the wireless communication equipment and are displayed in a time-amplitude curve graph mode; the doctor program controller calculates a brain wave curve graph according to a preset detection algorithm, and the detection algorithm calculates the line length or the area or the half-wave slope of the brain wave of the patient; comparing the size relationship between the calculation result of the line length or area or half-wave slope of the brain wave of the patient and a preset threshold value to judge whether the patient suffers from epilepsy;
the stimulation system comprises a doctor program-controlled instrument and a nerve stimulator, wherein the doctor program-controlled instrument controls the nerve stimulator to send a single stimulation command and detects the adaptability of a patient to pulse train parameters sent by the nerve stimulator, and the pulse train parameters comprise current, frequency, pulse width and duration; setting the number of bursts and parameters in the stimulation waveform according to the patient's adaptation to the burst parameters; the neural stimulator enters a self-response therapy state; the operation steps of the nerve stimulator in the self-response state are as follows:
in the brain wave sampling process of a patient, the neural stimulator defaults to amplitude detection written in chip hardware to judge abnormality, the neural stimulator is in a low-power-consumption operation state, and when the amplitude is detected to exceed the set amplitude in the chip hardware, the MCU is awakened to perform detection according to a preset detection scheme;
if the detection scheme detects that any one of the length, the area and the half-wave slope of the brain wave of the patient exceeds a preset threshold value, the doctor program controller controls the nerve stimulator to carry out response stimulation treatment according to the stimulation scheme;
when the detection scheme does not detect that any one of the length, the area and the half-wave slope of the brain wave of the patient exceeds a preset threshold and the abnormality does not occur for more than 5 minutes, the neural stimulator automatically enters a low power consumption mode of amplitude detection and is awakened when the amplitude is abnormal next time.
2. The system for automatically detecting and stimulating therapy for epilepsy as in claim 1, wherein said neurostimulator is an active implantable neurostimulator.
3. The system of claim 1, wherein the neurostimulator is configured to deliver a stimulation waveform comprising 1-6 bursts, each burst being adjustable in current, frequency, pulse width, and duration.
4. The system for automatically detecting and stimulating epilepsy according to claim 1, wherein the method for calculating whether the patient has epilepsy based on the brain wave length comprises the following steps:
firstly, a brain wave line length threshold value alpha is preset on a doctor program controller, and the time within a certain short time period t before a detection point is calculated
Brain wave average line length L1Wherein
Figure RE-DEST_PATH_IMAGE001
X is saidiThe voltage value of the brain wave of the patient;
secondly, calculating the average line length L of the brain waves in a certain long time period T before the detection point2Wherein
Figure RE-833142DEST_PATH_IMAGE002
；
Thirdly, calculating the detection result r of the brain wave line length1Wherein
Figure RE-DEST_PATH_IMAGE003
；
And fourthly, judging whether the brain wave line length detection result exceeds a threshold value alpha, and marking as judging the occurrence of epilepsy when the brain wave line length detection result exceeds the threshold value alpha.
5. The system for automatically detecting and stimulating epilepsy according to claim 1, wherein the method for calculating whether the patient has epilepsy based on brain wave area comprises the following steps:
firstly, calculating the average area S in a certain short time period t before the detection point1Wherein
Figure RE-78178DEST_PATH_IMAGE004
Mean value of brain wave voltage of middle patient
Figure RE-DEST_PATH_IMAGE005
X is saidiThe voltage value of the brain wave of the patient;
secondly, calculating the average area S in a certain long time period T before the detection point2Wherein
Figure RE-670965DEST_PATH_IMAGE006
；
Thirdly, calculating the area detection result r2Wherein
Figure RE-DEST_PATH_IMAGE007
；
And fourthly, judging whether the detection result of the line length exceeds a threshold value beta, and marking the line length as judging the occurrence of epilepsy when the detection result exceeds the threshold value beta.
6. The system for automatically detecting and stimulating epilepsy according to claim 1, wherein the method for calculating whether the patient has epilepsy based on the slope of half-wave of brain wave is as follows:
determining a given time period, sampling brain waves of a patient in the time period to obtain a curve graph, and dividing each peak value and adjacent peak-valley in the curve graph as a half-wave;
secondly, calculating the time length t of each half wavei，
Figure RE-331753DEST_PATH_IMAGE008
I.e. the frequency corresponding to the half-wave;
thirdly, calculating the amplitude of each half wave
Figure RE-DEST_PATH_IMAGE009
；
Fourthly, calculating the slope of each half wave, namely
Figure RE-224754DEST_PATH_IMAGE010
；
And fifthly, judging whether the calculation result of the slope of the half-wave exceeds a threshold gamma, and judging that the patient suffers from epilepsy when one slope exceeds the threshold gamma.
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