CN105496404B - Appraisal procedure based on brain-computer interface auxiliary CRS-R scale Auditory Startles - Google Patents
Appraisal procedure based on brain-computer interface auxiliary CRS-R scale Auditory Startles Download PDFInfo
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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
- A61B5/369—Electroencephalography [EEG]
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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
- A61B5/48—Other medical applications
Abstract
The invention discloses a kind of appraisal procedure based on brain-computer interface auxiliary CRS R scale Auditory Startles, including step：1) stimulation is selected, layout and the design of experimental paradigm；2) signal acquisition；3) data processing；4) statistical check evaluation criteria.The present invention induces the peculiar mismatch negative wave MMN and P300 of the mankind according to the strange experimental paradigm of the sense of hearing, restore the Auditory Startle appraisal procedure of scale CRS R with reference to stupor, using the scoring of Auditory Startle project in brain machine interface system and peak detection algorithm assessment CRS R, stupor recovery scale can be not only efficiently applied to assesses diagnosis and the tracking of rehabilitation efficacy and the selection of prognosis therapeutic scheme, it can also provide science objective detection data for graphic diagnosis routinely, to ensure the authenticity of testing result and validity.
Description
Technical field
The present invention relates to brain-computer interface technologies and the technical field of electro physiology event-related potentials, refer in particular to one kind
Appraisal procedure based on brain-computer interface auxiliary CRS-R scale Auditory Startles.
Background technology
After eighties of last century just finds electric (electroencephalogram, the EEG) signal of scalp brain, it is just applied
In the nervous system disease auxiliary diagnosis, brain function research etc..People realize big without traditional neuromuscular channel
Brain with it is extraneous it is direct exchange, and by study main rhythm and pace of moving things ingredient in EEG signals, various evoked brain potential signals and some
Mechanism, the spatial position of information source and its correlation that signal specific generates go to obtain direct letter of the brain to external environment reaction
The channel of breath.Brain-computer interface is to realize a this possible effective channel.
At present to the assessment Main Basiss behavior rating scale of state of consciousness observe, but behavior response easily because the patient feels and
Dyskinesia, tracheotomy, arousal level fluctuation or the interference of the factors such as fatiguability and mistaken diagnosis, there is that researches show that about 40% clinics
The patient for being diagnosed as vegetative state there are in fact consciousness sign.Stupor restores scale-revised edition (Coma Recovery
Scale-Revised, CRS-R) it is considered as stability and all higher " goldstandard " of rate of correct diagnosis in numerous scales.CRS-
R scales are divided into 6 sub- scales, the respectively sense of hearing, vision, movement, language, exchange, wake-up；Every sub- scale includes some projects
To detect the current state of consciousness of patient；For example the sub- scale of the sense of hearing includes：0- is reactionless, 1- Auditory Startles, 2- auditory localizations, 3-
The repeatable action of order, 4- is to ordering consistent action to follow；The detection of these projects is by clinician or professional assessment
Personnel, which judge Behavior Expression, provides corresponding scoring.Wherein Auditory Startle project is by giving sound outside patient's sight
(as clapped the hands) stimulates and observes the behavior reaction of blink or eyelid chatter caused by stimulation to carry out the Auditory Startle project evaluation.
This assessment may be inaccurate because habitually blink or dyskinesia generate interference to assessment result.
The existing strange experiment (Oddball Paradigm) of the sense of hearing is random in proportion using standard and deviation sonic stimulation
Appearance goes to induce event related potential (ERP) --- mismatch negative wave (mismatch negativity, MMN) and P300.Pass through
The different wave shape of analysis event related potential (ERP) goes assessment subject state of consciousness, but without being made for scale Auditory Startle
Corresponding assessment.
ERP Waveform Design Real-time Feedback brain-computer interface (BCI) system that the present invention is induced according to the strange experimental paradigm of the sense of hearing
System goes the Auditory Startle project in assessment CRS-R scales, and the score of Auditory Startle assessment is provided according to brain-computer interface result.It is right
In the assessment of environmental stimuli response, it is more sensitive, objective and accurate that the endogenic response ratio of brain plays behavior response.Therefore, it uses
The assessment of brain-computer interface auxiliary CRS-R scale Auditory Startles is objectively to obtain the scoring of this project in order to more accurate.
Event related potential (the MMN that the difficult point of the present invention is the selected of sonic stimulation, the subject of the disturbance of consciousness is induced
And P300) preclinical determine and the design of non-supervisory peak detection algorithm.Auditory estimating method in CRS-R scales and
The characteristics of disturbance of consciousness is tested, selects corresponding sonic stimulation and ERP incubation periods.The selection of sonic stimulation will as possible with CRS-R
Scale is consistent, just can ensure that the comparability of two methods.The incubation period precision of ERP needs to control in millisecond range, otherwise peak
Value detection algorithm is just unable to reach expected detection result.
Invention content
It is an object of the invention to be directed to too strong, the evaluated person of evaluator's subjectivity in existing clinical diagnosis technology to experience certainly
To the limiting of dyskinesia, existing ERP appraisal procedures are excessively general to the assessment of state of consciousness and can not overcome the disturbance of consciousness
Subject there are language understanding it is difficult the problems such as, provide it is a kind of based on brain-computer interface auxiliary CRS-R scale Auditory Startles assessment side
Method, the auditory stimulation form of the behavior evaluation of this method combination CRS-R, the BCI systems of composition strange (oddball) normal form of the sense of hearing
It goes to score to the Auditory Startle one of patient, and ensures the accuracy and objectivity of scoring.
To achieve the above object, technical solution provided by the present invention is：The CRS-R scale sense of hearings are assisted based on brain-computer interface
The appraisal procedure of scaring, includes the following steps：
1) stimulation is selected, layout and the design of experimental paradigm
According to two class sonic stimulation of the strange experimental paradigm selection standard of the sense of hearing and deviation, to be commented close to CRS-R behavior rating scales
Estimate mode, while also because complexsound is easier to induce in patients with brain injury than single sinusoidal sound loses matching wave, standard
Stimulation and deviation stimulation recorded environmental background noise and sound of clapping the hands, and with 4 respectively：1 ratio appears randomly in each thorn
Swash in sequence, every subject at least completes 10 tasks, and individual task includes at least 5 repetitive stimulation sequences；
2) signal acquisition
Scalp EEG signals, the brain of all channels are recorded using the EEG electrode caps of SynAmps2 amplifiers and 32 channels
Electric signal is dashed forward with auris dextra as reference, wherein " HEOGR " " HEOGL " is used for recording eyeball with " VEOGR " " VEOGL " two pairs of channels
Movement, to remove the artefact in EEG signals；During brain wave acquisition, the impedance values of all electrodes is all 5K Ω hereinafter, brain is electric
Signal carries out bandpass filtering with the frequency sampling of 250Hz in the range of 0.1 to 30Hz；
Auditory stimulation task is played using Microsoft Visual C++ software programmings program, screen occurs one first
Focus prompting subject focuses on, and cross mark then occurs and indicates entry into Preparatory work of experiment state, plays a task,
Online result is returned to subject and evaluator by non-supervisory peak detection algorithm, positive feedback loop the result is that cheerful and light-hearted applause,
Negativity feedback result is sigh sound；
3) data processing
After single stimulation task is presented, data are sent into computer in real time, and peak detection algorithm is immediately to data
It is handled, and positivity/negativity feedback sound is played according to result, peak detection algorithm is as follows：
1. passing through the filtering of 0.1Hz-10Hz by the collected raw EEG signal of Neuroscan amplifiers, while use time domain
Homing method removes pollution of the eye electricity to EEG signal；
2. selecting at least one channel, at least 50 data cells are built using the filtered EEG data of selected channel,
800ms after 200ms to stimulation, is the square that a channel is multiplied by 250 data points before each data cell is since stimulation
Battle array, this 50 data cells are averaged by the number of repetition each stimulated, the data cell matrix after finally obtaining 5 averagely；
3. to the data cell matrix after each be averaged, according to the time that mismatch negative wave MMN and P300 occur, exist first
A minimum value, i.e. trough are found in the 250ms-400ms periods, a maximum value, i.e. wave are found in subsequent 100ms
Peak, and the difference of the two is calculated, obtain the D difference of a port number × stimulation number in this way at the end of each experiment
Value matrix；
4. goal stimulus, that is, the stimulation voted to difference maximum are determined using the method for channel ballot；If there are two pierce
Sharp poll is the same, then compares the difference of both stimulations, that stimulation for selecting difference larger is goal stimulus；
4) statistical check evaluation criteria
Accuracy rate is got by the number of correctly responding for task divided by the number of whole tasks, in order to weigh accuracy rate
Whether significantly, by counting hit and the number of observation being not hit by and theoretical number, and Chi-square statistic is carried out according to following equation：
Wherein, foiAnd feiIt is the number of observation of i-th of classification and theoretical number, i=1,2 ..., k respectively；Herein,
Observation item is divided into hit and is not hit by two classes, fo1And fo2It is hit and the number of observation that is not hit by respectively, fe1And fe2Respectively
It is hit and the theoretical number being not hit by, degree of freedom is that classification item number k subtracts 1, as 1；It is carried out when using the BCI of 5 kinds of selections
Should be hit in the case where full-probability is equal and the number being not hit by all should be 4 and 16 when 20 subtasks judge；For
Show the conspicuousness of number of observation, i.e. probability P≤0.05, when degree of freedom is 1, test statistics χ2It needs to be more than 3.84,
That is in 20 subtasks, patient needs correctly to respond in >=8 tasks；
For complete 20 subtasks subject in, it is believed that accuracy more than the level of signifiance, and exist simultaneously MMN and
P300 waveforms, decide that subject obtains 1 point of scoring in Auditory Startle this project, otherwise scoring is 0.
In step 2), in signal acquisition process, before subject is first allowed to occupy stimulated side display, with display away from
From for 80-100cm, height of display is adjusted to head-up level, gives subject wears' electrode cap, is injected electrode cream with flat mouth syringe
Electrode cap embedded electrode, electrode cream injection finish, and give subject wears' earphone.
In step 4), to every subject, the EEG signals of 20 subtasks are acquired, and the frequency of 0.1-10Hz is carried out to it
Then each channel signal is divided into-100-700 milliseconds of data cell by rate range bandpass filtering, according to repeating for task
Number and stimulation number are averaged, and are divided into target and non-targeted ERP signals, draw their oscillogram, pass through incubation period, wave amplitude
These indexs judge whether subject produces rational ERP waveforms, and hit rate is notable, then judges by peak detection algorithm
The Auditory Startle of subject exists, and gives 1 point of scoring；If subject does not generate the ERP of peak detection algorithm accreditation
Waveform, and hit rate is not above the level of signifiance, it is believed that Auditory Startle is not present in it, gives 0 point of scoring；Another situation
Be waveform incubation period it is variant, but hit rate be more than the level of signifiance when, then subject needs to be further looked at.
Compared with prior art, the present invention having the following advantages that and advantageous effect：
1st, the mismatch negative wave and P300 that the present invention is induced according to the strange experiment of the sense of hearing, restores scale CRS- with reference to stupor
The Auditory Startle assessment of R, the standard stimulus and deviation selected in strange experimental paradigm stimulate, according to 4：1 ratio composition sequence
Random sequence of auditory stimuli.Event related potential ERP is induced, and given by peak detection algorithm by repeating playing stimulus sequence
Go out Auditory Startle this scoring, assist clinical assessment and the research of scale.
2nd, the present invention use the detection method based on brain-computer interface, overcome clinical lessons and experience detection to behavior ring
The shortcomings of susceptibility that should change is not high, subjectivity is too strong, meanwhile, with fMRI it is costly, it is not portable (can only be in large hospital
Nuclear magnetic resonance room carries out) and the phases such as stringent body requirement (cannot be with metallic support, many restrictions such as be not allowed to move)
Than can more easily be applied to clinically.
3rd, the present invention can not only be efficiently applied to the assessment diagnosis of stupor recovery scale and the tracking of rehabilitation efficacy, may be used also
To provide science objective detection data for graphic diagnosis routinely, to ensure the authenticity of testing result and validity.
Description of the drawings
Fig. 1 a are the schematic diagram of single listening task.
Fig. 1 b are the schematic diagram of single stimulus sequence.
Fig. 2 a are the average ERP oscillograms that 5 subjects induce.
Fig. 2 b are the response distribution map that 5 subjects induce.
Specific embodiment
With reference to specific embodiment, the invention will be further described.
The appraisal procedure based on brain-computer interface auxiliary CRS-R scale Auditory Startles described in the present embodiment, concrete condition
It is as follows：
1) stimulation is selected, layout and the design of experimental paradigm
Root is as close possible to CRS-R rows according to two class sonic stimulation of the strange experimental paradigm selection standard of the sense of hearing and deviation
For scale assessment mode, while also because complexsound is easier to induce in patients with brain injury than single sinusoidal sound loses matching
Wave, standard stimulus and deviation stimulation recorded environmental background noise (40dB) and sound (90dB) of clapping the hands, and with 4 respectively：1 ratio
It appears randomly in each stimulus sequence.Every subject at least completes 10 tasks, specific in the present embodiment to complete 10
A, individual task includes at least 5 repetitive stimulation sequences, in the present embodiment specially 5 repetitive stimulation sequences.Individual task
With the schematic diagram of stimulus sequence as illustrated in figs. 1A and ib.
2) signal acquisition
We are using the SynAmps2 amplifiers of Neuroscan Compumedics companies and the EEG electrode caps of 32 channels
(LT37) scalp EEG signals are recorded.The EEG signals of all channels are dashed forward with auris dextra as reference, wherein " HEOGR "
" HEOGL " is used for recording eye movement with " VEOGR " " VEOGL " two pairs of channels, to remove the artefact in EEG signals (EEG).
During brain wave acquisition, the impedance value of all electrodes is all below 5K Ω.EEG signals are with the frequency sampling of 250Hz, and 0.1
Bandpass filtering is carried out in the range of to 30Hz.
In signal acquisition process, before subject is first allowed to occupy stimulated side display, the distance with display is 80-
100cm, height of display is adjusted to head-up level, gives subject wears' electrode cap, with flat mouth syringe by electrode cream injecting electrode cap
Embedded electrode, electrode cream injection finish, and give subject wears' earphone.Using Microsoft Visual C++ software programming journeys
Sequence plays auditory stimulation task, and screen a focus prompting subject occurs and focuses on first, cross mark then occurs
Preparatory work of experiment state is indicated entry into, a task i.e. 5 repetitive stimulation sequences is played, is returned by non-supervisory peak detection algorithm
Online result is returned to subject and evaluator.For positive feedback loop the result is that cheerful and light-hearted applause, negativity feedback result is sigh sound.It is single
Full experiment task schematic diagram is shown in Fig. 1 a.
3) data processing
After single stimulation task is presented, data are sent into computer in real time, and peak detection algorithm is immediately to data
It is handled, and positivity/negativity feedback sound is played according to result.Peak detection algorithm is as follows：
1. passing through the filtering of 0.1Hz-10Hz by the collected raw EEG signal of Neuroscan amplifiers, while use time domain
Homing method removes pollution of the eye electricity to EEG signal.
2. selecting at least one channel, it is specifically chosen four channels (" Fz " " FCz " " Cz " " CPz "), profit in the present embodiment
It is (related to 50 stimulations of an experiment that 50 data cells are built with the filtered EEG data of selected channel：10
Round, each round include 1 offset stimulation and 4 standard stimulus), each data cell since stimulation before 200ms to
800ms after stimulation is the matrix that 4 channels are multiplied by 250 data points.By this 50 data cell by each stimulating
Number of repetition is averaged, the data cell matrix after finally obtaining 5 averagely.
3. to the data cell matrix after each be averaged, according to the time that mismatch negative wave MMN and P300 occur, exist first
A minimum value, i.e. trough are found in the 250ms-400ms periods, a maximum value, i.e. wave are found in subsequent 100ms
Peak, and the difference of the two is calculated, obtain the two-dimentional matrix of differences of one 4 × 5 in this way at the end of each experiment.
4. goal stimulus, that is, the stimulation voted to difference maximum are determined using the method for channel ballot；If there are two pierce
Sharp poll is the same, then compares the difference of both stimulations, that stimulation for selecting difference larger is goal stimulus.
4) statistical check evaluation criteria
Accuracy rate is got by the number of correctly responding for task divided by the number of whole tasks.In order to weigh accuracy rate
Significantly whether, we hit (hit) by statistics and are not hit by the number of observation (observed frequencies) of (miss)
With theoretical number (expected frequencies), and according to following equation carry out Chi-square statistic：
Wherein, foiAnd feiIt is the number of observation of i-th of classification and theoretical number, i=1,2 ..., k respectively；Herein,
Observation item is divided into hit and is not hit by two classes, fo1And fo2It is hit and the number of observation that is not hit by respectively, fe1And fe2Respectively
It is hit and the theoretical number being not hit by, degree of freedom is that classification item number k subtracts 1, as 1.It is carried out when using the BCI of 5 kinds of selections
Should be hit in the case where full-probability is equal and the number being not hit by all should be 4 and 16 when 20 subtasks judge.For
Show the conspicuousness of number of observation, i.e. probability P≤0.05, test statistics χ2(degree of freedom=1) needs to be more than 3.84, i.e., 20
In subtask, subject needs correctly to respond in >=8 tasks.
In subject for completing 20 subtasks, it is believed that accuracy exists simultaneously MMN more than the level of signifiance
With P300 waveforms, decide that subject obtains 1 point of scoring in Auditory Startle this project, otherwise scoring is 0.
To every subject, we acquire the EEG signals of 20 subtasks, and carry out the frequency range of 0.1-10Hz to it
Then each channel signal is divided into-100-700 milliseconds of data cell by bandpass filtering, according to repeat task number and
Stimulation number is averaged, and is divided into target and non-targeted ERP signals, draws their oscillogram, passes through the fingers such as incubation period, wave amplitude
Mark judges whether subject produces rational ERP waveforms, and hit rate is significantly (40%), then judges by peak detection algorithm
The Auditory Startle of subject exists, and gives 1 point of scoring.If subject does not generate the ERP of peak detection algorithm accreditation
Waveform, and hit rate is not above the level of signifiance, it is believed that Auditory Startle is not present in it, gives 0 point of scoring.Another situation
Be waveform incubation period it is variant, but hit rate be more than the level of signifiance when, then subject needs to be further looked at.
In the present embodiment, after 5 subjects have carried out 30 subtasks, mean hit rate up to 84.6 ± 7.8%, far more than
The level of signifiance (40%).The average ERP waveforms and distribution map of 5 subjects, can be with from Fig. 2 a, 2b as shown in Fig. 2 a, 2b
Clearly see in target waveform and not contained containing MMN, P300 rather than target waveform.Therefore, the ERP waveforms of subject are very
Stablize, and all there are Auditory Startles.
The examples of implementation of the above are only the preferred embodiments of the invention, and the implementation model of the present invention is not limited with this
It encloses, therefore the variation that all shape, principles according to the present invention are made, it should all cover within the scope of the present invention.
Claims (2)
1. the appraisal procedure based on brain-computer interface auxiliary CRS-R scale Auditory Startles, which is characterized in that include the following steps：
1) stimulation is selected, layout and the design of experimental paradigm
According to two class sonic stimulation of the strange experimental paradigm selection standard of the sense of hearing and deviation, for close to CRS-R behavior rating scales assessment side
Formula, while also because complexsound is easier to induce in patients with brain injury than single sinusoidal sound loses matching wave, standard stimulus
And deviation stimulation recorded environmental background noise respectively and sound of clapping the hands, and with 4：1 ratio appears randomly in each stimulation sequence
In row, every subject at least completes 10 tasks, and individual task includes at least 5 repetitive stimulation sequences；
2) signal acquisition
Scalp EEG signals, the brain telecommunications of all channels are recorded using the EEG electrode caps of SynAmps2 amplifiers and 32 channels
It number is dashed forward with auris dextra as reference, wherein " HEOGR " " HEOGL " is used for recording eyeball fortune with " VEOGR " " VEOGL " two pairs of channels
It is dynamic, to remove the artefact in EEG signals；During brain wave acquisition, the impedance values of all electrodes is all 5K Ω hereinafter, brain telecommunications
Number with the frequency sampling of 250Hz, and bandpass filtering is carried out in the range of 0.1 to 30Hz；
Auditory stimulation task is played using Microsoft Visual C++ software programmings program, a focus occurs first in screen
Prompting subject focuses on, and cross mark then occurs and indicates entry into Preparatory work of experiment state, a task is played, by non-
The peak detection algorithm of supervision returns to online result to subject and evaluator, and positive feedback loop is the result is that cheerful and light-hearted applause, negativity
Feedback result is sigh sound；
3) data processing
After single stimulation task is presented, data are sent into computer in real time, and peak detection algorithm immediately carries out data
Processing, and positivity/negativity feedback sound is played according to result, peak detection algorithm is as follows：
1. passing through the filtering of 0.1Hz-10Hz by the collected raw EEG signal of Neuroscan amplifiers, while returned with time domain
Method removes pollution of the eye electricity to EEG signal；
2. selecting at least one channel, at least 50 data cells are built using the filtered EEG data of selected channel, each
Data cell since stimulation before 800ms after 200ms to stimulation, be the matrix that a channel is multiplied by 250 data points, will
This 50 data cells are averaged by the number of repetition each stimulated, the data cell matrix after finally obtaining 5 averagely；
3. to the data cell matrix after each be averaged, according to the time that mismatch negative wave MMN and P300 occur, exist first
A minimum value, i.e. trough are found in the 250ms-400ms periods, a maximum value, i.e. wave are found in subsequent 100ms
Peak, and the difference of the two is calculated, obtain the D difference of a port number × stimulation number in this way at the end of each experiment
Value matrix；
4. goal stimulus, that is, the stimulation voted to difference maximum are determined using the method for channel ballot；If there are two what is stimulated
Poll is the same, then compares the difference of both stimulations, that stimulation for selecting difference larger is goal stimulus；
4) statistical check evaluation criteria
Accuracy rate is got by the number of correctly responding for task divided by the number of whole tasks, in order to whether weigh accuracy rate
Significantly, by counting hit and the number of observation being not hit by and theoretical number, and Chi-square statistic is carried out according to following equation：
Wherein, foiAnd feiIt is the number of observation of i-th of classification and theoretical number, i=1,2 ..., k respectively；Herein, it observes
Project is divided into hit and is not hit by two classes, fo1And fo2It is hit and the number of observation that is not hit by respectively, fe1And fe2It is life respectively
The theoretical number being not hit by is neutralized, degree of freedom is that classification item number k subtracts 1, as 1；It has been carried out 20 times when using the BCI of 5 kinds of selections
Should be hit in the case where full-probability is equal and the number being not hit by is 4 and 16 respectively when task judges；In order to show
The conspicuousness of number of observation, i.e. probability P≤0.05, when degree of freedom is 1, test statistics χ2It needs more than 3.84, i.e., 20 times
In task, subject needs correctly to respond in >=8 tasks；
In subject for completing 20 subtasks, it is believed that accuracy exists simultaneously MMN and P300 waves more than the level of signifiance
Shape, decide that subject obtains 1 point of scoring in Auditory Startle this project, otherwise scoring is 0.
2. the appraisal procedure according to claim 1 based on brain-computer interface auxiliary CRS-R scale Auditory Startles, feature exist
In：In step 2), in signal acquisition process, before subject is first allowed to occupy stimulated side display, the distance with display is
80-100cm, height of display is adjusted to head-up level, gives subject wears' electrode cap, with flat mouth syringe by electrode cream injecting electrode
Cap embedded electrode, electrode cream injection finish, and give subject wears' earphone.
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| CN104605839A (en) * | 2015-02-05 | 2015-05-13 | 广州市润杰医疗器械有限公司 | Coma patient analepsia prediction method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| WO2006122304A1 (en) * | 2005-05-11 | 2006-11-16 | Bio-Logic Systems Corp. | Neurophysiological central auditory processing evaluation system and method |
| CN101464729A (en) * | 2009-01-05 | 2009-06-24 | 清华大学 | Independent desire expression method based on auditory sense cognition neural signal |
| WO2011160222A1 (en) * | 2010-06-22 | 2011-12-29 | National Research Council Of Canada | Cognitive function assessment in a patient |
| CN104605839A (en) * | 2015-02-05 | 2015-05-13 | 广州市润杰医疗器械有限公司 | Coma patient analepsia prediction method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| WO2021064214A1 (en) * | 2019-10-04 | 2021-04-08 | Icm (Institut Du Cerveau Et De La Moelle Épinière) | System for the automatic evaluation of cognition and consciousness of an individual through external stimulations |
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