CN105496404A - Assessment method of auxiliary CRS-R scale auditory shock based on brain-computer interface - Google Patents
Assessment method of auxiliary CRS-R scale auditory shock based on brain-computer interface Download PDFInfo
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Abstract
The invention discloses an assessment method of auxiliary CRS-R scale auditory shock based on a brain-computer interface. The assessment method comprises following steps of: 1) selecting simulation, arranging and designing an experimental paradigm; 2), collecting signals; 3) performing data processing; 4) counting inspecting evaluation standards. The assessment method of auxiliary CRS-R scale auditory shock based on the brain-computer interface has following beneficial effects: based on an auditory extraneous experimental paradigm, mismatch negative waves MMN and P300, peculiar to human race, are induced; in combination with an auditory shock assessment method of a coma recovery scale CRS-R, scores of CRS-R auditory shock items are accessed by adoption of the brain-computer interface and a peak detection algorithm; and therefore, the method can not only be effectively used for assessment diagnoses of the coma recovery scale, tracking of recovery effect and selections of a prognosis treatment scheme but also provide scientific and objective detection data to the conventional scale diagnoses in order to ensure authenticity and effectiveness of detection results..
Description
Technical field
The present invention relates to the technical field of brain-computer interface technology and electro physiology event-related potentials, refer in particular to a kind of appraisal procedure of assisting CRS-R scale Auditory Startle based on brain-computer interface.
Background technology
After eighties of last century just finds scalp brain electricity (electroencephalogram, EEG) signal, it is just applied to the aspects such as nervous system disease auxiliary diagnosis, brain function research.People exchange with the direct of the external world without the need to realizing brain by traditional neuromuscular channel, and go to obtain brain to the channel of the direct information of outside environment reaction by the mechanism of rhythm and pace of moving things composition, various evoked brain potential signal and some signal specific generation main in research EEG signals, the locus of information source and mutual relation thereof.Brain-computer interface realizes a this possible effective channel.
At present the assessment Main Basis behavior rating scale of state of consciousness is observed, but behavior response is the mistaken diagnosis because of factor interference such as patient's sensation and the dyskinesia, tracheotomy, arousal level fluctuation or fatiguabilities easily, and the clinical diagnosis having research to show about 40% is that in fact the patient of vegetative state exists consciousness sign.Stupor is recovered scale-revised edition (ComaRecoveryScale-Revised, CRS-R) and is considered to stability and rate of correct diagnosis in numerous scale all higher " goldstandard ".CRS-R scale is divided into 6 sub-scales, is respectively audition, vision, motion, and language exchanges, wakes up; Every sub-scale comprises some projects to detect the current state of consciousness of patient; The sub-scale of such as audition comprises: 0-is reactionless, 1-Auditory Startle, 2-auditory localization, 3-order repeatably action, and 4-follows the consistent action of order; The detection of these projects to be judged Behavior Expression by clinician or expert panelist and provides corresponding scoring.Wherein Auditory Startle project stimulates by giving sound (as clapping the hands) outside patient's sight line and observe by stimulating the behavior reaction of nictation or the eyelid chatter caused to carry out the Auditory Startle project evaluation.This assessment may because of habitually nictation or the dyskinesia to assessment result produce interference and inaccurate.
The strange experiment of existing audition (OddballParadigm) employing standard and deviation sonic stimulation occur bringing out event related potential (ERP) in proportion at random---mismatch negativity (mismatchnegativity, MMN) and P300.Go to assess tested state of consciousness by the different wave shape analyzing event related potential (ERP), but do not make corresponding assessment for scale Auditory Startle.
The present invention goes to assess the Auditory Startle project in CRS-R scale according to ERP Waveform Design Real-time Feedback brain-computer interface (BCI) system that the strange experimental paradigm of audition induces, and provides the mark of Auditory Startle assessment according to brain-computer interface result.For the assessment of environmental stimuli response, it is more responsive, objective and accurate that the endogenic response ratio of brain plays behavior response.Therefore, brain-computer interface is adopted to assist the assessment of CRS-R scale Auditory Startle to be objectively obtain the scoring of this project in order to more accurate.
Difficult point of the present invention is that tested the brought out event related potential (MMN and P300) that is selected, disturbance of consciousness of sonic stimulation is preclinical and determines and the design of non-supervisory peak detection algorithm.According to the Auditory estimating method in CRS-R scale and the tested feature of disturbance of consciousness, select corresponding sonic stimulation and ERP incubation period.The selection of sonic stimulation is as far as possible consistent with CRS-R scale, just can guarantee the comparability of two kinds of methods.Precision incubation period of ERP needs to control in millisecond scope, otherwise peak detection algorithm just cannot reach the Detection results of expection.
Summary of the invention
The object of the invention is to for evaluator's subjectivity in existing clinical diagnosis technology too strong, evaluated person self is subject to dyskinetic restriction, existing ERP appraisal procedure is too general and cannot overcome that disturbance of consciousness is tested exists the problems such as language understanding difficulty to the assessment of state of consciousness, a kind of appraisal procedure of assisting CRS-R scale Auditory Startle based on brain-computer interface is provided, the method is in conjunction with the auditory stimulus form of the behavior evaluation of CRS-R, the BCI system forming audition strange (oddball) normal form goes to mark to the Auditory Startle one of patient, and guarantee accuracy and the objectivity of scoring.
For achieving the above object, technical scheme provided by the present invention is: the appraisal procedure of assisting CRS-R scale Auditory Startle based on brain-computer interface, comprises the following steps:
1) stimulation is selected, the design of layout and experimental paradigm
According to the strange experimental paradigm selection standard of audition and deviation two class sonic stimulation, for close to CRS-R behavior rating scale assessment mode, simultaneously also because in patients with brain injury bring out easier than single sinusoidal sound of complexsound loses coupling ripple, standard stimulus and deviation stimulate and recorded environmental background noise respectively and to clap the hands sound, and appear in each stimulus sequence at random with the ratio of 4:1, every experimenter at least completes 10 tasks, and individual task at least comprises 5 repetitive stimulation sequences;
2) signals collecting
The EEG electrode cap of SynAmps2 amplifier and 32 passages is adopted to record scalp EEG signals, the EEG signals of all passages is all dashed forward as reference with auris dextra, wherein " HEOGR " " HEOGL " and " VEOGR " " VEOGL " two pairs of passages are used for recording ocular movement, to remove the artefact in EEG signals; In brain wave acquisition process, the resistance value of all electrodes is all below 5K Ω, and EEG signals with the frequency sampling of 250Hz, and carries out bandpass filtering in the scope of 0.1 to 30Hz;
MicrosoftVisualC++ software programming program is adopted to play auditory stimulus task, first screen occurs that a focus prompting experimenter focuses one's attention on, occur that cross mark represents subsequently and enter Preparatory work of experiment state, play a task, online result is returned to experimenter and evaluator by non-supervisory peak detection algorithm, positive feedback loop result is cheerful and light-hearted applause, and negativity feedback result is sigh sound;
3) date processing
After single stimulation task presents, data are sent in computer in real time, and peak detection algorithm processes data immediately, and play positivity/negativity feedback sound according to result, and peak detection algorithm concrete steps are as follows:
1. the raw EEG signal collected by Neuroscan amplifier, through the filtering of 0.1Hz-10Hz, removes the pollution of eye electricity to EEG signal with time domain homing method simultaneously;
2. at least 1 passage is selected, the filtered EEG data of selected passage is utilized to build at least 50 data cells, each data cell front 200ms from stimulation terminates rear 800ms to stimulation, it is the matrix that a passage is multiplied by 250 data points, these 50 data cells are average by the number of repetition of each stimulation, finally obtain 5 average after data cell matrix;
3. to each average after data cell matrix, according to the time that mismatch negativity MMN and P300 occurs, first within the 250ms-400ms time period, a minima is found, i.e. trough, a maximum is found in 100ms subsequently, i.e. crest, and the difference both calculating, namely obtain the two-dimentional matrix of differences of a port number × stimulation number like this at the end of each experiment;
4. adopt the method for passage ballot to determine target stimulus, namely vote to the maximum stimulation of difference; If there are two polls stimulated the same, then compare these the two kinds differences stimulated, that stimulation selecting difference larger is target stimulus;
4) statistical test evaluation criteria
Whether accuracy rate is got divided by the number of times of whole task by the number of times of correctly responding of task, remarkable in order to weigh accuracy rate, by statistics hit and the number of observation of not hitting and theoretical number of times, and carries out Chi-square statistic according to following formula:
Wherein, fo
iand fe
ithe number of observation of i-th classification and theoretical number of times respectively, i=1,2 ..., k; Here, observation item is divided into hit and does not hit two classes, fo
1and fo
2the number of observation being hit respectively and not hitting, fe
1and fe
2the theoretical number of times being hit respectively and not hitting, degree of freedom is that classification item number k subtracts 1, is 1; When the BCI that use 5 kinds is selected has carried out 20 subtasks judgement, should be that hitting with the number of times do not hit should be all 4 and 16 when full-probability is equal; In order to show the significance of number of observation, i.e. probability P≤0.05, when degree of freedom is 1, statistic of test χ
2need to be greater than 3.84, namely in 20 subtasks, needs of patients correctly responds in>=8 tasks;
For completing in the experimenter of 20 subtasks, more than significant level, and there is MMN and P300 waveform in the rate that praises simultaneously, just judges that experimenter obtains 1 point of scoring in this project of Auditory Startle, otherwise to mark be 0.
In step 2) in, in signal acquisition process, before first allowing experimenter occupy stimulated side display, be 80-100cm with the distance of display, height of display is adjusted to the level of looking squarely, to subject wears's electrode cap, with flat mouth syringe by electrode cream injecting electrode cap embedded electrode, electrode cream injects complete, to subject wears's earphone.
In step 4) in, to every experimenter, gather the EEG signals of 20 subtasks, and it is carried out to the frequency range bandpass filtering of 0.1-10Hz, then each channel signal is divided into the data cell of-100-700 milliseconds, average with stimulation number of times according to the task number of times repeated, be divided into the ERP signal of target and non-targeted, draw their oscillogram, pass through incubation period, these indexs of wave amplitude, judge whether experimenter creates rational ERP waveform by peak detection algorithm, and hit rate is remarkable, then judge that the Auditory Startle of experimenter exists, and give the scoring of 1 point, if experimenter does not produce the ERP waveform of peak detection algorithm accreditation, and hit rate does not exceed significant level, thinks that it does not exist Auditory Startle, gives the scoring of 0 point, another situation is that the incubation period of waveform is variant, but when hit rate exceedes significant level, then experimenter needs to be observed further.
Compared with prior art, tool has the following advantages and beneficial effect in the present invention:
1, the mismatch negativity that induces according to the strange experiment of audition of the present invention and P300, the Auditory Startle assessment of scale CRS-R is recovered in conjunction with stupor, standard stimulus in selected strange experimental paradigm and deviation stimulate, according to the sequence of auditory stimuli that the ratio formation order of 4:1 is random.Bring out event related potential ERP by repeat playing stimulus sequence, and provide this scoring of Auditory Startle by peak detection algorithm, the clinical assessment of auxiliary scale and research.
2, the present invention adopts the detection method based on brain-computer interface,, the shortcoming such as subjectivity too strong not high to the sensitivity of behavior response change that overcome that clinical lessons and experience detect, simultaneously, with fMRI costly, not portable (can only carry out at the nuclear magnetic resonance room of large hospital) and strict health require (can not be with metal rack, forbidden many restrictions such as moving) etc. compare, can be applied to clinically more easily.
3, the present invention not only effectively can be applied to the stupor recovery assessment diagnosis of scale and the tracking of rehabilitation efficacy, can also science be provided objectively to detect data for graphic diagnosis routinely, to ensure verity and the effectiveness of testing result.
Accompanying drawing explanation
Fig. 1 a is the schematic diagram of single listening task.
Fig. 1 b is the schematic diagram of single stimulus sequence.
Fig. 2 a is the average ERP oscillogram that 5 experimenters bring out.
Fig. 2 b is the response scattergram that 5 experimenters bring out.
Detailed description of the invention
Below in conjunction with specific embodiment, the invention will be further described.
The appraisal procedure of assisting CRS-R scale Auditory Startle based on brain-computer interface described in the present embodiment, its concrete condition is as follows:
1) stimulation is selected, the design of layout and experimental paradigm
Root is according to the strange experimental paradigm selection standard of audition and deviation two class sonic stimulation, for as far as possible close to CRS-R behavior rating scale assessment mode, simultaneously also because in patients with brain injury bring out easier than single sinusoidal sound of complexsound loses coupling ripple, standard stimulus and deviation stimulate and recorded environmental background noise (40dB) respectively and to clap the hands sound (90dB), and appear at random in each stimulus sequence with the ratio of 4:1.Every experimenter at least completes 10 tasks, specifically completes 10 in the present embodiment, and individual task at least comprises 5 repetitive stimulation sequences, is specially 5 repetitive stimulation sequences in the present embodiment.The schematic diagram of individual task and stimulus sequence as illustrated in figs. ia and ib.
2) signals collecting
We adopt the EEG electrode cap (LT37) of the SynAmps2 amplifier of NeuroscanCompumedics company and 32 passages to record scalp EEG signals.The EEG signals of all passages is all dashed forward as reference with auris dextra, and wherein " HEOGR " " HEOGL " and " VEOGR " " VEOGL " two pairs of passages are used for recording ocular movement, to remove the artefact in EEG signals (EEG).In brain wave acquisition process, the resistance value of all electrodes is all below 5K Ω.EEG signals with the frequency sampling of 250Hz, and carries out bandpass filtering in the scope of 0.1 to 30Hz.
In signal acquisition process, before first allowing experimenter occupy stimulated side display, be 80-100cm with the distance of display, height of display is adjusted to the level of looking squarely, to subject wears's electrode cap, with flat mouth syringe by electrode cream injecting electrode cap embedded electrode, electrode cream injects complete, to subject wears's earphone.MicrosoftVisualC++ software programming program is adopted to play auditory stimulus task, first screen occurs that a focus prompting experimenter focuses one's attention on, occur that cross mark represents subsequently and enter Preparatory work of experiment state, play a task i.e. 5 repetitive stimulation sequences, return online result to experimenter and evaluator by non-supervisory peak detection algorithm.Positive feedback loop result is cheerful and light-hearted applause, and negativity feedback result is sigh sound.Fig. 1 a is shown in by single full experiment task schematic diagram.
3) date processing
After single stimulation task presents, data are sent in computer in real time, and peak detection algorithm processes data immediately, and play positivity/negativity feedback sound according to result.Peak detection algorithm concrete steps are as follows:
1. the raw EEG signal collected by Neuroscan amplifier, through the filtering of 0.1Hz-10Hz, removes the pollution of eye electricity to EEG signal with time domain homing method simultaneously.
2. at least 1 passage is selected, specifically select four passages (" Fz " " FCz " " Cz " " CPz ") in the present embodiment, utilizing the filtered EEG data of selected passage to build 50 data cells (stimulates relevant to 50 that one is tested: 10 round, each round comprises 1 skew to be stimulated and 4 standard stimuluses), each data cell front 200ms from stimulation terminates rear 800ms to stimulation, is the matrix that 4 passages are multiplied by 250 data points.These 50 data cells are average by the number of repetition of each stimulation, finally obtain 5 average after data cell matrix.
3. to each average after data cell matrix, according to the time that mismatch negativity MMN and P300 occurs, first within the 250ms-400ms time period, a minima is found, i.e. trough, a maximum is found in 100ms subsequently, i.e. crest, and the difference both calculating, namely obtain the two-dimentional matrix of differences of 4 × 5 like this at the end of each experiment.
4. adopt the method for passage ballot to determine target stimulus, namely vote to the maximum stimulation of difference; If there are two polls stimulated the same, then compare these the two kinds differences stimulated, that stimulation selecting difference larger is target stimulus.
4) statistical test evaluation criteria
Accuracy rate is got divided by the number of times of whole task by the number of times of correctly responding of task.Whether remarkable in order to weigh accuracy rate, we by statistics hit (hit) and the number of observation (observedfrequencies) and the theoretical number of times (expectedfrequencies) that do not hit (miss), and carry out Chi-square statistic according to following formula:
Wherein, fo
iand fe
ithe number of observation of i-th classification and theoretical number of times respectively, i=1,2 ..., k; Here, observation item is divided into hit and does not hit two classes, fo
1and fo
2the number of observation being hit respectively and not hitting, fe
1and fe
2the theoretical number of times being hit respectively and not hitting, degree of freedom is that classification item number k subtracts 1, is 1.When the BCI that use 5 kinds is selected has carried out 20 subtasks judgement, should be that hitting with the number of times do not hit should be all 4 and 16 when full-probability is equal.In order to show the significance of number of observation, i.e. probability P≤0.05, statistic of test χ
2(degree of freedom=1) needs to be greater than 3.84, and namely in 20 subtasks, experimenter needs correctly to respond in>=8 tasks.
For completing in the experimenter of 20 subtasks, we praise rate more than significant level, and there is MMN and P300 waveform simultaneously, just judge that experimenter obtains 1 point of scoring in this project of Auditory Startle, otherwise to mark be 0.
To every experimenter, we gather the EEG signals of 20 subtasks, and it is carried out to the frequency range bandpass filtering of 0.1-10Hz, then each channel signal is divided into the data cell of-100-700 milliseconds, average with stimulation number of times according to the task number of times repeated, be divided into the ERP signal of target and non-targeted, draw their oscillogram, pass through incubation period, the indexs such as wave amplitude, judge whether experimenter creates rational ERP waveform by peak detection algorithm, and hit rate significantly (40%), then judge that the Auditory Startle of experimenter exists, and give the scoring of 1 point.If experimenter does not produce the ERP waveform of peak detection algorithm accreditation, and hit rate does not exceed significant level, thinks that it does not exist Auditory Startle, gives the scoring of 0 point.Another situation is that the incubation period of waveform is variant, but when hit rate exceedes significant level, then experimenter needs to be observed further.
In the present embodiment, after 5 experimenters have carried out 30 subtasks, mean hit rate has reached 84.6 ± 7.8%, far exceedes significant level (40%).The average ERP waveform of these 5 experimenters and scattergram, as shown in Fig. 2 a, 2b, can clearly see containing MMN, P300 in target waveform, but not target waveform do not contain from Fig. 2 a, 2b.Therefore, the ERP waveform of experimenter is highly stable, and all there is Auditory Startle.
The examples of implementation of the above are only the preferred embodiment of the present invention, not limit practical range of the present invention with this, therefore the change that all shapes according to the present invention, principle are done, all should be encompassed in protection scope of the present invention.
Claims (3)
1. assist the appraisal procedure of CRS-R scale Auditory Startle based on brain-computer interface, it is characterized in that, comprise the following steps:
1) stimulation is selected, the design of layout and experimental paradigm
According to the strange experimental paradigm selection standard of audition and deviation two class sonic stimulation, for close to CRS-R behavior rating scale assessment mode, simultaneously also because in patients with brain injury bring out easier than single sinusoidal sound of complexsound loses coupling ripple, standard stimulus and deviation stimulate and recorded environmental background noise respectively and to clap the hands sound, and appear in each stimulus sequence at random with the ratio of 4:1, every experimenter at least completes 10 tasks, and individual task at least comprises 5 repetitive stimulation sequences;
2) signals collecting
The EEG electrode cap of SynAmps2 amplifier and 32 passages is adopted to record scalp EEG signals, the EEG signals of all passages is all dashed forward as reference with auris dextra, wherein " HEOGR " " HEOGL " and " VEOGR " " VEOGL " two pairs of passages are used for recording ocular movement, to remove the artefact in EEG signals; In brain wave acquisition process, the resistance value of all electrodes is all below 5K Ω, and EEG signals with the frequency sampling of 250Hz, and carries out bandpass filtering in the scope of 0.1 to 30Hz;
MicrosoftVisualC++ software programming program is adopted to play auditory stimulus task, first screen occurs that a focus prompting experimenter focuses one's attention on, occur that cross mark represents subsequently and enter Preparatory work of experiment state, play a task, online result is returned to experimenter and evaluator by non-supervisory peak detection algorithm, positive feedback loop result is cheerful and light-hearted applause, and negativity feedback result is sigh sound;
3) date processing
After single stimulation task presents, data are sent in computer in real time, and peak detection algorithm processes data immediately, and play positivity/negativity feedback sound according to result, and peak detection algorithm concrete steps are as follows:
1. the raw EEG signal collected by Neuroscan amplifier, through the filtering of 0.1Hz-10Hz, removes the pollution of eye electricity to EEG signal with time domain homing method simultaneously;
2. at least 1 passage is selected, the filtered EEG data of selected passage is utilized to build at least 50 data cells, each data cell front 200ms from stimulation terminates rear 800ms to stimulation, it is the matrix that a passage is multiplied by 250 data points, these 50 data cells are average by the number of repetition of each stimulation, finally obtain 5 average after data cell matrix;
3. to each average after data cell matrix, according to the time that mismatch negativity MMN and P300 occurs, first within the 250ms-400ms time period, a minima is found, i.e. trough, a maximum is found in 100ms subsequently, i.e. crest, and the difference both calculating, namely obtain the two-dimentional matrix of differences of a port number × stimulation number like this at the end of each experiment;
4. adopt the method for passage ballot to determine target stimulus, namely vote to the maximum stimulation of difference; If there are two polls stimulated the same, then compare these the two kinds differences stimulated, that stimulation selecting difference larger is target stimulus;
4) statistical test evaluation criteria
Whether accuracy rate is got divided by the number of times of whole task by the number of times of correctly responding of task, remarkable in order to weigh accuracy rate, by statistics hit and the number of observation of not hitting and theoretical number of times, and carries out Chi-square statistic according to following formula:
Wherein, fo
iand fe
ithe number of observation of i-th classification and theoretical number of times respectively, i=1,2 ..., k; Here, observation item is divided into hit and does not hit two classes, fo
1and fo
2the number of observation being hit respectively and not hitting, fe
1and fe
2the theoretical number of times being hit respectively and not hitting, degree of freedom is that classification item number k subtracts 1, is 1; When the BCI that use 5 kinds is selected has carried out 20 subtasks judgement, should be that hitting with the number of times do not hit should be all 4 and 16 when full-probability is equal; In order to show the significance of number of observation, i.e. probability P≤0.05, when degree of freedom is 1, statistic of test χ
2need to be greater than 3.84, namely in 20 subtasks, experimenter needs correctly to respond in>=8 tasks;
For completing in the experimenter of 20 subtasks, more than significant level, and there is MMN and P300 waveform in the rate that praises simultaneously, just judges that experimenter obtains 1 point of scoring in this project of Auditory Startle, otherwise to mark be 0.
2. appraisal procedure of assisting CRS-R scale Auditory Startle based on brain-computer interface according to claim 1, it is characterized in that: in step 2) in, in signal acquisition process, before first allowing experimenter occupy stimulated side display, be 80-100cm with the distance of display, height of display is adjusted to the level of looking squarely, to subject wears's electrode cap, with flat mouth syringe by electrode cream injecting electrode cap embedded electrode, electrode cream injects complete, to subject wears's earphone.
3. appraisal procedure of assisting CRS-R scale Auditory Startle based on brain-computer interface according to claim 1, it is characterized in that: in step 4) in, to every experimenter, gather the EEG signals of 20 subtasks, and it is carried out to the frequency range bandpass filtering of 0.1-10Hz, then each channel signal is divided into the data cell of-100-700 milliseconds, average with stimulation number of times according to the task number of times repeated, be divided into the ERP signal of target and non-targeted, draw their oscillogram, pass through incubation period, these indexs of wave amplitude, judge whether experimenter creates rational ERP waveform by peak detection algorithm, and hit rate is remarkable, then judge that the Auditory Startle of experimenter exists, and give the scoring of 1 point, if experimenter does not produce the ERP waveform of peak detection algorithm accreditation, and hit rate does not exceed significant level, thinks that it does not exist Auditory Startle, gives the scoring of 0 point, another situation is that the incubation period of waveform is variant, but when hit rate exceedes significant level, then experimenter needs to be observed further.
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