WO2016090396A1 - Procédé de quantification de la capacité de perception d'une personne - Google Patents

Procédé de quantification de la capacité de perception d'une personne Download PDF

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Publication number
WO2016090396A1
WO2016090396A1 PCT/AT2015/050290 AT2015050290W WO2016090396A1 WO 2016090396 A1 WO2016090396 A1 WO 2016090396A1 AT 2015050290 W AT2015050290 W AT 2015050290W WO 2016090396 A1 WO2016090396 A1 WO 2016090396A1
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Prior art keywords
person
stimulus
eeg data
determined
stimuli
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PCT/AT2015/050290
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German (de)
English (en)
Inventor
Christoph GUGER
Günter EDLINGER
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Guger Christoph
Edlinger Günter
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Publication of WO2016090396A1 publication Critical patent/WO2016090396A1/fr

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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
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • A61B5/7267—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems involving training the classification device
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0048—Detecting, measuring or recording by applying mechanical forces or stimuli
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/16—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state
    • 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]
    • A61B5/377—Electroencephalography [EEG] using evoked responses
    • 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
    • A61B5/4005—Detecting, measuring or recording for evaluating the nervous system for evaluating the sensory system
    • 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
    • A61B5/4824—Touch or pain perception evaluation
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients

Definitions

  • the invention relates to a method according to the preamble of patent claim 1.
  • different measuring methods are known which can be used to detect different mental activities of a person and, based on this, trigger actions.
  • Also known from the state of the art are individual, so-called brain-computer interfaces, which are used to detect, process and also visualize the processes taking place in the brain of a person in different ways.
  • the essential background of the invention is to examine patients in the late stage of neurological diseases, for example in the late stage of amyotrophic lateral sclerosis (ALS), or also patients with consciousness or cognitive impairments, to what extent their individual subjective perception ability at a certain time.
  • ALS amyotrophic lateral sclerosis
  • the determination of these abilities is of the utmost relevance to the patient in question, since depending on the personal perception ability, communication possibilities or control possibilities adapted to him or her can be used.
  • the object of the present invention is to provide a rapid and simple method for quantifying the ability to perceive, which has a effective detection of cognitive ability, and is largely independent of individual differences between individual subjects. It is another object of the invention to give the person the opportunity to use the acquired skills to answer questions for the control of certain body functions.
  • a method for quantifying the perceptibility of a person
  • the subject is given mental activities to be performed in the presence of a stimulus, depending on the nature of that stimulus;
  • a kind of stimulus is selected from the set of possible types of stimuli, in particular according to random criteria,
  • - EEG data of the person are determined and recorded within a time range before, during or after the application of the respective stimulus, wherein the time range preferably has a duration of 1 to 10 seconds, and
  • a measure is determined as to whether the EEG data associated with a particular stimulus are distinguishable from the EEG data associated with a stimulus of different types
  • the invention has the significant advantage that the perception ability of a person can be quantified independently of whether he is capable of actually carrying out certain motor actions.
  • the present test can be easily adapted to different test conditions by the person different mental activities are applied, each leading to different results in the EEG data.
  • individually different intellectual activities can also be used for the quantification in order to obtain as meaningful a value as possible.
  • the test can be adapted to different additional sensory disorders of the person.
  • a prosthesis or a robot exists on an area of the body of the person with whom the body of the person is irritated at a location of the body or with which a part of the person's body is manipulated, this location of the body being determined by the result determined by means of classification.
  • an activation stimulus is assigned in the form of a stimulus at a location of the body part in question or in the form of a manipulation of the body part in question.
  • a simple method of determining the measure involves determining the measure by examining the likelihood that the application of the classification analysis to the individual EEG data associated with the types of stimuli will each indicate the correct stimulus.
  • a particularly simple embodiment of the invention which only requires the functionality of the hearing, provides that the set of types of stimuli is given by different tones, in particular with different duration, frequency and volume, in frequencies audible to a human and the respective tone the person is played.
  • a further embodiment of the invention which requires a slight tactile sensation, provides that the set of the types of stimuli comprises vibratory exposures to different body parts and / or with different intensity and / or duration applied to the person by means of vibration units.
  • Another embodiment of the invention which presupposes a visual sensation, provides that the set of the types of stimuli comprises visual stimuli for an eye or both eyes and / or with different intensity and / or duration, which the person uses by means of a screen or by means of a screen Bulbs are applied.
  • a further embodiment of the invention which presupposes an electrical stimulus sensation, provides that the set of the types of stimuli comprises electrical stimuli at different body parts and / or with different intensity and / or duration, which are applied to the person by means of electrical stimulators.
  • Particularly distinctive and easily performed by subjects mental activities that achieve particularly meaningful results in connection with the present invention are, for example:
  • a particularly advantageous preprocessing of the EEG data comprising a plurality of EEG signals and EEG channels provides that an evaluation of the recorded EEG data is performed by the individual EEG data of the individual EEG channels taken at the same time a signal vector are summarized,
  • a particularly advantageous, individual adaptation to the respective person provides that the weight vectors and the weight values, as well as possibly the additional summand, are adapted to the respective person, so that the extent determined in the classification analysis is maximized,
  • the weight vectors, the weight values, and optionally the further summand are iteratively adapted until the classification analysis delivers a maximum measure of distinctness based on the already determined test data.
  • the EEG data are subjected to bandpass filtering on a channel by channel basis before the assessment by means of classification analysis, the filtered signal, in particular exclusively , Contains frequencies between 8 Hz and 30 Hz.
  • the EEG data or the data underlying the classification analysis in particular the results of an averaging, the evoked potentials derived from the EEG data or the EEG data after performing an event-related desynchronization or the EEG data, preferably the Person and / or an operator conducting the procedure.
  • a particularly rapid, simple and efficient implementation can be performed if the measure of whether the EEG data associated with a particular stimulus is distinguishable from the EEG data associated with a stimulus of different types is performed using one of the following types of classification analysis:
  • the method is carried out on several, in particular consecutive, days, if necessary several times, in particular with the same stimuli, whereby the measure of the perceptual capacity of the person for each day is determined separately and the measure that indicates the greatest perceptibility is used as a measure of the perceptual capacity of the person.
  • the invention also relates to a data carrier on which a method for carrying out a method according to the invention according to one of the preceding claims is stored.
  • Fig. 1 shows schematically an example of an arrangement for carrying out a method according to the invention.
  • 2 shows the procedure for the further processing of EEG data up to the determination of test values.
  • Fig. 3 shows the control unit shown in Fig. 1 in detail.
  • Fig. 1 shows a person, hereinafter referred to as subject 1, whose perception is to be quantified.
  • subject 1 an EEG hood 21 was attached to it, which are connected by means of a respective EEG cable connections 22a, 22zz to a test unit 20.
  • subject 1 headphones 1 1 were placed by means of which acoustic stimuli S, for example in the form of tones or tone sequences, are applied to the subjects 1.
  • the headphones 1 1 and the test unit 20 are connected to a control unit 10 which controls the delivery of the stimuli S and receives the test values transmitted to the test unit 20.
  • the test unit 20 can be configured and adapted to the respective subjects 1.
  • a set of different stimuli S is set.
  • tones with different pitches are set as stimuli S, which can be played by means of a loudspeaker 11 or headphones 11 to the test person 1.
  • a loudspeaker 11 or headphones 11 to the test person 1.
  • only two different pitches are given as possible stimuli S in the exemplary embodiment shown.
  • stimuli S can also be used within the scope of the invention.
  • the subject 1 can perceive certain features of sounds such as duration, frequency and volume only limited.
  • the set of types of stimuli S can thus also be determined by different tones, In particular, with different duration, frequency and volume, are given in audible to a human frequencies and the respective sound is played to the subject.
  • stimuli S it is therefore also possible to use other visually, electrically and tactile or otherwise perceptible stimuli as stimuli S.
  • the amount of the types of stimuli S can be applied to the subject by means of vibration units, for example, in the form of vibration exposures to different body parts and / or with different intensity and / or duration.
  • the subject 1 is informed of which reactions he has to make in response to the respective stimuli S.
  • This message can be done in different ways, for example by explanation in the form of a voice message or by displaying the desired procedure on a screen 12.
  • One possible order to the subject 1 is, for example, the instruction, with a high tone to the right hand and at to think a deep tone to the left hand.
  • a possible task may be to mentally count in the presence of a tactile stimulus by a vibration unit in a given body area.
  • an order adapted to the subject 1 can be created.
  • EEG electrodes are placed on the head of the subject 1.
  • a sample arrangement with electrodes in the present example with 27 electrodes applied.
  • the individual derivatives determined by the electrodes are led to an amplifier unit 201, amplified and digitized.
  • the individual stimuli S are applied to the subject 1 in order to familiarize him / her with all the stimuli S.
  • the subject 1 is played both the high and the low tone and then he is told what reaction is expected of him, namely,
  • a random unit 101 selects one type of stimulus S and transmits a respective selection signal to a stimulus unit 102, which transmits the stimulus S to the headphones 11 in the form of an electrical analog signal.
  • the test person 1 was auditioned for a second in the first test step for one second.
  • the subject 1 recognizes the high tone as such and thinks during the playback of the high tone or thereafter according to his right hand.
  • all of the EEG channels will be used for further investigation.
  • the beginning of this time window may be before, during or after the stimulus. In the present example, the time window begins 100 ms before the start of the stimulus.
  • the samples obtained from the EEG measurement are channel-wise subjected to bandpass filtering 202. It is done before or after sampling a filtering that frequency components of the signal, which are smaller than 8 Hz and greater than 30 Hz, are strongly attenuated.
  • individual values derived from the totality of the signals for example a signal vector s comprising all individual channel-specific signal values of the EEG signal, can be used for a discriminant analysis.
  • a discriminant analysis carried out in this way can, in principle, be used to quantify the ability to perceive.
  • the present preferred embodiment of the invention provides a simplification that allows implementation of the method with significantly less resource consumption.
  • all signal values of the individual EEG channels recorded at the same time are combined to form a common signal vector s.
  • the signal vectors s each comprise 27 individual signal values, namely one per EEG channel.
  • weight vectors g a , g d are determined for the respective person, which have the same size as the signal vectors s.
  • the weight vectors each have 27 elements or entries.
  • one weighting unit 203a, 203b, 203c, 203d For each individual recording or sampling time point during the time window, in each case one weighting unit 203a, 203b, 203c, 203d generates a scale product p a , p b , p c , p d of the determined signal vector s with each of the weight vectors g a , g d created.
  • scale products p a , p b , p c , p d are stored in downstream buffer memories 204 a, 204 b, 204 c, 204 d . stored separately for the respective weight vector g a , g d .
  • the variance v a , v b , v c , v d is determined in each case for these scale products p a , p b , p c , p d lying in the buffer memories 204 a, 204 b, 204 c, 204 d .
  • This weighting unit 206 forms a weighted sum of the individual variances v a, v b, v c, v d wherein each of the variances in each case with a weight value w a, w b, w c, w d is drawn from a further weight vector w.
  • the weighting unit 206 adds another one if necessary add further summands s, so that at the output of the weighting unit 206, a scalar value T is applied.
  • the sequence of the values determined within the time window is subsequently referred to as the test value and transmitted from the test unit 20 to the control unit 10 and assigned by it to the respective type of stimulus S.
  • the weight vectors g a , g d , the further weight vector W and the further summand S are referred to below as individual data and determined separately for each subject 1.
  • the actual determination of the individual data g a, g d, w, s is performed in the present embodiment in an optimization procedure, and is described in more detail below and is advantageously carried out after carrying fewer test steps and can be optionally repeated for adaptation to training results of the test person. 1 With this advantageous procedure it can be ensured that the discriminant analysis can be carried out with numerically little effort.
  • the test values T obtained in the respective test step are assigned to the respective type of stimulus S.
  • headphones 1 1 played a high tone as stimulus S.
  • the type of stimulus is transmitted to a memory control unit 104, which forwards the test value T to a first memory 103a for storage. If a lower tone than stimulus S is specified in a second or further test step, the memory control unit 104 forwards the test value T to a second memory 103b.
  • a multiplicity of different test values T are present in the two memories 103a, 103b.
  • discriminant analysis 105 By means of discriminant analysis 105, to which the individual test values T stored in the memories 103a, 103b are fed, a distinguishing criterion G can be determined, which distinguishes between the test values T obtained from the individual types of stimuli S, for example a high tone and test values. the one by one low tone, allows.
  • the discriminant analysis 105 also provides a measure M of the distinctness of the test values T to be separated, which for the following reasons is considered to be measure M for the perception capability of the subject 1.
  • the discriminant analysis 105 gives a maximum measure M of distinctness.
  • the relevant subject 1 understood the order and was able to perceive the individual applied stimuli S and reacted to them in a targeted manner. However, if the respective subject 1 has no ability to perceive at all, no different mental activities can be ascertained.
  • the discriminant analysis 105 supplies a distinguishing criterion G, it can not be concluded from the fulfillment or non-fulfillment of the distinguishing criterion G by the respective test value T that the respective stimulus S has been determined.
  • the measure M for the distinctness of the individual test values is consequently small.
  • the procedure may be as follows: starting from randomly predetermined starting values for the individual values g a , g d , w, s or starting from The individual data, namely the weight vectors g a , g d , the further weight vectors w and the further summand s, can be adapted to the starting values of already tested probands 1 with high perception capability until the discriminant analysis 105 is based on a first set of EEG Data provides a maximum measure of distinctness.
  • the first set of EEG data need not necessarily contain all the EEG data collected by subject 1.
  • the individual data g a , g d , w, s can also be redetermined after certain time intervals. This is particularly advantageous if the presented method is used after the quantification of the perceptual ability for further communication. This process of adaptation of the individual data g a , g d , w, s can be repeated iteratively until an optimal distinctness of the test values is present.
  • any optimization method can be used to optimize the individual values g a , g d , w, s. Good results have been achieved by the invention with a method which is known from the literature and whose contents are incorporated in this application:
  • the optimization process may be controlled by a non-illustrated optimization unit of the control unit 10, which each individual values g a, g d, w, s and modifying iteratively in each case a renewed creation of the test data T by the test unit 20 starts.
  • the test value T determined in the test step can be subjected to the discriminating criterion G determined by the discriminant analysis 105 by a comparison unit 106 after the respective test step.
  • the result E of the application of the criterion G to the test value T can then be displayed to the test person 1 or to a third party or else brought to the knowledge.
  • the result can be graphically displayed on screens 12, 13, for example.
  • the discriminant analysis can also be performed again and the differentiation criterion G can be reset.
  • the determination of the distinguishing criterion G is basically not required for the quantification of the perception ability, but can be used to determine the response of the subject 1 in each case.
  • This circumstance makes use of a special development of the invention, which, after the quantification of the perception ability of the subject 1, additionally strives for continuous communication with the subject 1. After the quantification of the perception ability of the subject 1, this person can be asked further questions for the purposes of the communication and the subject 1 can be given mental activities to be carried out in the affirmative or negative of this question. These questions can for example be shown to the subject 1 on their screen 12 or transmitted via the headphones 1 1.
  • the subject 1 uses in response the same mental activities that were previously used in the quantification of the perceptual ability, since a sufficient distinctness and a distinguishing criterion G for distinguishing the answers or the test values T have already been established with regard to these mental activities.
  • the questions addressed to subjects 1 are usually questions that are provided with given answers, for example the answers "yes” and "no". It is also possible to agree with the subject 1 a more complex response scheme with a greater number of discernible mental activities than answers, if they can be determined reliably and distinguishably.
  • Subject 1 following individual questions, carries out mental activities which are detected by the EEG and classified by means of the previously determined discriminant analysis 105, i. the discrimination criterion G originating from the discriminant analysis 105 is applied to the test value and the result E is determined. Depending on the result E, a different answer of the subject 1 to the question asked is assumed. The answers or the determined results E of the classification are kept available to the questioner and displayed on the screens 12, 13, as well as possibly also on the subject.
  • a linear discriminant analysis was used by way of example for determining the measure M for distinctness.
  • this is not mandatory. Rather, different types of classification analysis, with which a separation of different test values is possible, can be used.
  • support vector machines "Hidden Markov model and support vector machine based decoding of finger movements using electrocorticography; Wissel T, Pfeiffer T, Frysch R, Knight RT, Chang EF, Hinrichs H, Rieger JW, Rose G. J Neural Eng. 2013 Oct; 10 (5): 056020. doi: 10. 1088 / 1741-2560 / 10/5/056020. Epub 2013 Sep 18.
  • PMID: 24045504 [PubMed - in process] "or Neural Networks” CM Bishop, Neural Networks for Pattern Recognition, 1995. Clarendon "for classification analysis to determine a measure M for the distinctness.
  • the measure M can also be determined by examining with what probability the application of the classification analysis 105 to the individual EEG data associated with the types of stimuli indicates the correct stimulus. For this purpose, the classification analysis 105 is subsequently applied individually to all determined EEG data, with a classification result being determined in each case. Subsequently, it is examined whether the respective classification result agrees with the stimulus that was applied to the patient during the determination of the EEG data. The ratio of the correct assessments to the total number of individual EEG data determined or the number of applied stimuli can be used as measure M.
  • Evoked potentials are calculated by averaging the EEG data of a specific stimulus and presented as an EP curve.
  • the software overlays the evoked potentials of two classes and therefore differences can be easily recognized. On the one hand, this allows to see whether the expected physiological response has occurred and, furthermore, to detect whether differences exist. Furthermore, a statistical test is performed indicating whether the data is distinguishable. Statistically significant differences are marked in the graph.
  • Event-related desynchronization is calculated for each class by filtering the data in a typical frequency range (eg alpha range 8-12 Hz, beta range 16-24 Hz, ). Then the power is calculated and this data is averaged over all repetitions. Subsequently, averaging in the time domain is performed to smooth the curves. This change in power is related to a reference interval before the mental activity and therefore indicates the change in the band performance due to the activity being performed. This result is still evaluated with a statistical test, so that only significant changes are displayed. Both event-related desynchronization and evoked potentials can be visualized and can serve as feedback to the patient to better perform activities. It is important for the operator to know if the patient is doing the job properly and he can take corrective action. Furthermore, the operator can judge physiological effects based on his experience.
  • a typical frequency range eg alpha range 8-12 Hz, beta range 16-24 Hz, .
  • the invention also provides that after the determination of the measure M for the ability to perceive, the results of the previously performed measured values can be used further.
  • a procedure makes sense only if it has been established for the person concerned that the measure determined exceeds a predetermined threshold, since otherwise it can not be ruled out that the brain waves measured by the person are measured purely randomly and without deliberate control on the basis of the stimuli were.
  • the classification of measured value results individually determined for the person can be meaningfully continued to be used.
  • EEG data of the person concerned are continuously determined.
  • the period of detection can also be limited to individual time ranges, for example, to avoid movements during sleep.
  • the EEG data are classified according to the already performed classification analysis 105, whereby different classification results can be determined in each case.
  • an activation stimulus is created, which causes the relevant body movement.
  • functional electrostimulation, orthoses, prostheses or robots are used for the application of activation stimuli A.
  • the activation stimulus may also trigger a stimulus on a body site corresponding to the stimulus to provide the subject with feedback.
  • an activation stimulus A assigned to this result E is applied to the subject 1 from the classification. It is thus possible, for example, for a stimulus S, which requires the person 1 to make a movement of the forearm, to assign an activation stimulus A, which is a stimulus on the forearm or a stimulation of the forearm by means of functional electrostimulation, orthosis, prosthesis, robot triggers a corresponding movement of the forearm.

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Abstract

L'invention concerne un procédé dans lequel on prescrit une série d'au moins deux types possibles, perceptibles de façon différente, de stimuli (S) applicables à des sujets d'expérience (1), et dans lequel on soumet au sujet d'expérience (1) des expériences de pensée qui doivent être réalisées en présence d'un stimulus (S) en fonction du type de ce stimulus (S), on associée les données d'EEG déterminées à chaque fois ou des données qui en découlent au type respectif de stimulus (S). Au moyen d'une analyse de classification (105), on détermine une mesure (M) pour savoir si les données EEG, associées à un stimulus particulier (S), peuvent être distinguées d'un stimulus (S) de divers types de données EEG associées. D'autres données EEG de la personne (1) sont déterminées et enregistrées et les données EEG enregistrées sont classées par l'analyse de classification (105) effectuée précédemment et, en présence d'un résultat déterminé (E), on effectue à partir de la classification une action associée à ce résultat (E).
PCT/AT2015/050290 2014-12-09 2015-11-12 Procédé de quantification de la capacité de perception d'une personne WO2016090396A1 (fr)

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ATA50893/2014 2014-12-09
ATA50893/2014A AT516020B1 (de) 2014-12-09 2014-12-09 Verfahren zur Quantifizierung der Wahrnehmungsfähigkeit einer Person

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AT520374A1 (de) * 2017-09-06 2019-03-15 Dipl Ing Dr Techn Christoph Guger Bestimmung der Rangfolge der Wahrnehmungsintensität von Stimuli aus einer Testmenge von Stimuli bei einem Probanden

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