EP1931251A2 - Procede et ensemble permettant d'analyser un signal bioelectromagnetique variant dans le temps - Google Patents

Procede et ensemble permettant d'analyser un signal bioelectromagnetique variant dans le temps

Info

Publication number
EP1931251A2
EP1931251A2 EP06791304A EP06791304A EP1931251A2 EP 1931251 A2 EP1931251 A2 EP 1931251A2 EP 06791304 A EP06791304 A EP 06791304A EP 06791304 A EP06791304 A EP 06791304A EP 1931251 A2 EP1931251 A2 EP 1931251A2
Authority
EP
European Patent Office
Prior art keywords
signal
signal components
frequency ranges
reference time
bioelectromagnetic
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP06791304A
Other languages
German (de)
English (en)
Inventor
Alfred Scherbaum
José Alberto GONZALÈZ-HERNANDÈZ
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Heinrich Heine Universitaet Duesseldof
Original Assignee
Heinrich Heine Universitaet Duesseldof
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Heinrich Heine Universitaet Duesseldof filed Critical Heinrich Heine Universitaet Duesseldof
Publication of EP1931251A2 publication Critical patent/EP1931251A2/fr
Withdrawn legal-status Critical Current

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Classifications

    • 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]
    • A61B5/372—Analysis of electroencephalograms
    • A61B5/374—Detecting the frequency distribution of signals, e.g. detecting delta, theta, alpha, beta or gamma waves

Definitions

  • the invention relates to a method and an arrangement for analyzing a time-varying bioelectromagnetic signal.
  • the invention relates to a method and an arrangement for analyzing electroencephalographic signals.
  • independent claims relates to
  • bioelectromagnetic signals are understood as meaning electrical and / or magnetic signals detectable by means of corresponding sensors and detectors, such as electrodes, which originate in the electrical activity of a biological object such as, for example, a beating heart or another muscle Brain or peripheral nerves. Since moving electrical charges induce magnetic fields, the following is always spoken of electromagnetic signals, even if in many applications actually only an electrical potential or its change over time is measured.
  • Frequencies are exchanged, wherein the different frequency ranges commonly referred to as ⁇ -, ß-, ⁇ - and ⁇ -areas. It is generally known e.g. the so-called oc state when the main brain activity occurs at frequencies in the ⁇ -range and the human is in a relaxed state in which he is particularly adaptive.
  • Measuring signals can act.
  • DE 692 28 823 T2 discloses a method for the non-invasive detection of cerebral phenomena in which dynamic phase relations are characterized after bandpass filters of electroencephalographic signals within the filtered signals.
  • bioelectromagnetic signals there is the problem of so-called “biological referencing”, that is the relationship of the measured signals to suitable reference points for the purpose of obtaining relevant information, e.g. for controlling a machine, as a statement about the effect of drugs or as a diagnostically relevant parameter, the basis for the later
  • the signals Conventionally, to obtain relevant information from the measured signals, the signals to empirically derived data, e.g. typical averages, for example, by checking whether a measured value lies within a typical value range.
  • empirically derived data e.g. typical averages
  • bioelectromagnetic signals are naturally subject to some noise and are individually different in strength and severity, so that it is often difficult to obtain meaningful information solely by comparison with reference data.
  • the object of the invention is a method and an arrangement for analyzing a time-varying bioelectromagnetic signal, which detects over a certain time interval and be split by means of a band-pass filtering in at least two different with respect to their frequency ranges signal components to specify, which allow information in a simple manner, such as control information for the control of a machine, a prosthesis or the like. or to gain diagnostically meaningful parameters.
  • the object is achieved by a method in which at least one reference time of the first type is determined in at least one of the signal components different in their frequency ranges and the values of at least two signal components differing in their frequency ranges at the specific reference time of the first type predetermined evaluation criteria are related to each other.
  • the invention is based on the surprising finding that important information can be obtained from bioelectromagnetic signals when the bandpass filtered signals are related to each other by considering the behavior of certain signal components at characteristic reference times, but the reference times are not "externally" predetermined but be determined according to specifiable selection criteria from the detected bioelectromagnetic signal itself.
  • the step of determining a reference time in a signal component comprises determining any extreme values and / or inflection points which may be present in the time interval in the signal component.
  • Signals such as the signal measured by means of an electrocardiograph, have characteristic curve shapes whose sections can be easily identified by means of turning points within a cycle (eg the so-called QRS complex or the ST segment in the electrocardiogram or the general as P and N peaks (P as positive, N as negative) in the evoked potential curve in electroencephalography).
  • At least one second reference instant of the first type is determined in at least one second signal component which differs from the first with respect to its frequency range, whereupon the values of at least two signal components differing with regard to their frequency ranges be related to each other in the first and second reference times of the first kind.
  • the signal under study is the detection of the change in potential evoked in response to a simple physical or cognitive stimulus, as evidenced by electroencephalographs, a functional analysis of the signal may be obtained, e.g.
  • the step of relating the values assumed by different signal components in the reference time (s) of the first kind comprises determining differences between the ones
  • Signal components and / or determining tendencies such as rising or falling in the individual signal components. Such differences and tendencies can be excellently visualized with visualization methods known per se, if necessary after the solution of the so-called "inverse problem", so that certain information can clearly emerge and be easily read.
  • at least one N ⁇ N matrix of the first type can then be created, in which the values of each signal component are entered at the N reference times of the first kind and from which different functional and temporal ones
  • the bioelectromagnetic signal to be analyzed has been recorded by means of a multichannel acquisition device in such a way that it is possible to analyze the signal with regard to the spatial distribution of its sources in the bioelectromagnetically active object being examined, it can advantageously be determined in which regions of the object under investigation one of the determined Reference points a particular, in the generation of a characteristic change of a certain of the signal components differing in their frequency ranges resulting activity was present. It can also be determined which regions of the examined object are active at the reference time determined with respect to a signal component for generating signal components of other frequency ranges.
  • At least one reference time of at least one second type is determined.
  • the time points at which brainwaves in the ⁇ , ⁇ and ⁇ frequency ranges, which propagate at different speeds in the brain, each have their own so-called C-peak can be selected as reference times of the first type , as reference times of the second kind, the times at which brain waves in the ⁇ -, ß- and ⁇ -frequency range, the respective P-peaks, and as reference times of the third kind, the times at which the brain waves in ⁇ -, ß- and ⁇ -frequency range Reach N-tips.
  • the step of relating at least two signal components differing with respect to their frequency ranges can also take place for the reference times of the second and possibly third type, and not necessarily to those for the reference time (s) first type identical predetermined evaluation criteria.
  • the method has proven to be particularly advantageous for use with such bioelectromagnetic signals that occur in response to an external stimulus supplied to the bioelectromagnetic signal generating the bioelectromagnetic active object.
  • the stimulus is repeatedly supplied to the object, that correspondingly several times a bioelectromagnetic signal is detected and that the signal to be analyzed is finally formed from suitable averaging of the detected signals.
  • averaging methods are considered, the specific
  • bioelectromagnetic signal to be analyzed was an electroencephalogram recorded by a multichannel electroencephalograph, good results were obtained using simple cognitive stimuli, especially simple visual stimuli such as e.g. achieved a changing with a certain frequency checkerboard pattern, which was shown to a person to be examined achieved.
  • the object is achieved by an arrangement for analyzing a time-varying bioelectromagnetic signal detected over a certain time interval comprising an analog or digital band-pass filter for splitting the signal into at least two signal components different in their frequency ranges, Means for automatically determining at least one reference time of the first type in at least one of the different with respect to their frequency ranges
  • the means for determining a reference time can be designed such that they enable the determination of extreme values and / or turning points which may be present in a considered signal component.
  • the means for determining a reference time are designed such that they allow the determination of a plurality of reference times of the same or different type in different signal components differing with regard to their frequency ranges.
  • the means for automatically relating the values of at least two signal components different in their frequency ranges may be arranged to allow the values of any signal components different in their frequency ranges to be related at reference times of any kind.
  • the means for relating the values of different signal components at the reference time (s) may be arranged to determine the differences between the signal components and / or to determine trends such as increasing or decreasing in the individual ones
  • the bandpass filter may be arranged to split the bioelectromagnetic signal into N (N e N + ) signal components different in frequency ranges, preferably N being at least equal
  • the arrangement expediently comprises at least one memory unit into which at least one N ⁇ N matrix of the first type can be written, which contains the values of each signal component at N reference times of the same type.
  • the arrangement can advantageously means for determining and / or visualization of the regions of the examined object, in which one of the specific reference times a particular, in the production of a particular differing in terms of their frequency ranges
  • Signal components resulting activity include.
  • the above-mentioned means for determining and / or visualizing the regions of the examined object in which a specific activity is present at one of the determined reference times can be designed such that they enable the regions of the examined object to be identified and / or visualized with respect to a signal component specific reference time for the generation of signal components of other frequency ranges are active.
  • the independent claims 27 to 30 each relate to an advantageously designed electroencephalographies, electromyographs, magnetoencephalographs and electroneurographs.
  • the subordinate claim 31 relates to a machine-readable memory containing the commands required for automatically carrying out a method according to the invention.
  • FIG. 1 shows a schematic diagram which illustrates the state of the art (a) in comparison with a basic idea of the invention (b) using the example of an electroencephalographically measured, visually evoked potential.
  • Fig. 2 is a schematic diagram for illustrating the classical course of the electroencephalographic measurement of a visually evoked potential.
  • Fig. 3 shows in four fields a) to d) purely schematically the basic
  • Fig. 5 shows purely schematically the structure of an N x N matrix according to an advantageous embodiment of the invention.
  • FIG. 6 shows purely schematically, using the example of electroencephalographic data, some of the information obtainable after the inverse problem has been solved, namely according to the prior art (FIG. 6a) and according to the method according to the invention (FIG. 6b).
  • Fig. 7 shows the example of electroencephalographic data in the form of
  • Sectional images of the present invention recoverable information (7b) compared to the prior art (Fig. 7a).
  • Fig. 1 shows schematically the procedure for obtaining such electroencephalographic data by visual evocation of potentials in the brain. This will be a subject about a certain Time zone shown a checkerboard pattern in which at a certain frequency, typically 1 Hz, the fields swap their colors, so black fields white and white fields are black.
  • a certain frequency typically 1 Hz
  • This simple visual stimulus evokes a potential in the brain of the subject and thus a bioelectric signal in the sense of the invention, which can be measured with a conventional electroencephalography, for example.
  • 30 Ag / AgCI electrodes are placed at various points of the subject's skull using the international 10/10 electrode placement system.
  • the neurons in the brain form various neural networks (indicated by the reference numeral 10 in Fig. 1), using waves of different frequencies substantially in a range between 0.5 and 70 Hz for communication with each other.
  • this frequency range is usually subdivided into specific subregions, so that one can designate the individual networks according to the frequencies of the waves used by their neurons for communication among themselves as ⁇ , ⁇ , ⁇ , ⁇ 1 and ⁇ networks .
  • the various components can be isolated by bandpass filtering.
  • Fig. 1 denoted by "C1”
  • C1 Potential range
  • P1 the first peak in the positive range
  • N 1 peak is in the negative potential range.
  • a pictorial representation as shown in FIG. 1 can be provided, for example in the form of an incision or a virtual three-dimensional image of the skull and brain, and then the area in which the strongest on average
  • FIG. 2 shows the classical course of the electroencephalographic measurement of a visually evoked potential.
  • Fig. 2a shows the two different
  • Checkerboard pattern A and B which, as indicated in Fig. 2b, alternately e.g. at a frequency of 1 Hz to an eye of an examined person, in the example of Fig. 2b the left eye.
  • FIG. 3 shows, in four partial diagrams, purely schematically the basic method steps for obtaining the electroencephalographic data then considered according to the invention.
  • This visual stimulus generates an electrical activity in the brain of the person being examined, that is to say the neurons of different neural networks are activated, and they oscillate to communicate with each other
  • first certain reference times in the exemplary embodiment shown reference time of the first, second and third type, are selected, namely
  • reference times are selected within the various signal components at all, to which then the behavior of the other signal components is considered, so the values of their
  • Frequency range differing signal components in the selected reference times are set according to specifiable evaluation criteria to each other.
  • evaluation criteria may be the determination of differences between the signal components and / or the determination of tendencies such as rising or falling in the individual signal components.
  • an N x N matrix can be created in which the diagonal is the reference time of the same kind, e.g. the P1 peaks, represented. On the diagonal of the matrix, therefore, the values of those signal components are entered, which at the respective time just their own
  • FIG. 6 By solving the aforementioned inverse problem and corresponding visualization techniques, as shown in FIG. 6 of course only two-dimensionally, virtual 3D images can be constructed which contain valuable information.
  • Fig. 6a By solving the aforementioned inverse problem and corresponding visualization techniques, as shown in FIG. 6 of course only two-dimensionally, virtual 3D images can be constructed which contain valuable information.
  • Fig. 6a After averaging across all signal components, one would obtain only an image as shown in Fig. 6a, in which the averaged behavior of all the different networks at a given reference time, e.g. the P1 tip is shown.
  • Reference time e.g. the P1 tip
  • the P1 tip delivers. Horizontally next to it the temporal development of the same network is readable, namely at the times, at which other networks go through the respective P1-peak.
  • Medications caused changes in the behavior of the networks can not be determined in the classical way, since after averaging and In reference to external reference data no deviation was found, while using the dynamic self-referencing certain disease patterns or certain drugs significant differences in the spatial effect temporal development of the various network activities, so that, for example, in a person suffering from a particular disease or even for such a disease assessed persons at a time when a particular network passes through the P1 peak, already another network in becomes active in a certain area, while such activity does not show in healthy persons.
  • FIGS. 7a and 7b while sick and healthy persons showed no significant deviation in an evaluation of electroencephalographically obtained data according to the prior art (FIG. 7a), it permits the invention
  • Behavior of the various networks can contain revealing information, obtained by the invention for the first time and further evaluation of e.g. can be made accessible by a doctor.
  • a doctor has been shown that under certain test conditions between healthy and sick patients, although no deviation in the spatial activation of certain areas in the brain, but a difference in the temporal behavior of the networks can be found at the dynamic reference time points.

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  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Medical Informatics (AREA)
  • Biophysics (AREA)
  • Pathology (AREA)
  • Engineering & Computer Science (AREA)
  • Biomedical Technology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Physics & Mathematics (AREA)
  • Molecular Biology (AREA)
  • Surgery (AREA)
  • Animal Behavior & Ethology (AREA)
  • General Health & Medical Sciences (AREA)
  • Public Health (AREA)
  • Veterinary Medicine (AREA)
  • Psychiatry (AREA)
  • Psychology (AREA)
  • Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)

Abstract

L'invention concerne un procédé et un ensemble permettant d'analyser un signal bioélectromagnétique variant dans le temps, lequel signal a été enregistré pendant un intervalle de temps défini puis est séparé, par un filtrage passe-bande, en au moins deux composantes se distinguant par leurs gammes de fréquences. Selon ladite invention, au moins un moment de référence de ce type est déterminé dans au moins une des composantes du signal se distinguant par leurs gammes de fréquence selon des critères de sélection prédéfinissables et les valeurs d'au moins deux composantes du signal se distinguant par leurs gammes de fréquence sont mises en rapport selon des critères d'analyse prédéfinissables au moment de référence déterminé.
EP06791304A 2005-08-04 2006-08-04 Procede et ensemble permettant d'analyser un signal bioelectromagnetique variant dans le temps Withdrawn EP1931251A2 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102005037326 2005-08-04
PCT/DE2006/001370 WO2007014558A2 (fr) 2005-08-04 2006-08-04 Procede et ensemble permettant d'analyser un signal bioelectromagnetique variant dans le temps

Publications (1)

Publication Number Publication Date
EP1931251A2 true EP1931251A2 (fr) 2008-06-18

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EP06791304A Withdrawn EP1931251A2 (fr) 2005-08-04 2006-08-04 Procede et ensemble permettant d'analyser un signal bioelectromagnetique variant dans le temps

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US (1) US20090221929A1 (fr)
EP (1) EP1931251A2 (fr)
DE (1) DE112006002659A5 (fr)
WO (1) WO2007014558A2 (fr)

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TWI563973B (zh) * 2015-12-02 2017-01-01 麗東生技股份有限公司 生物訊號檢測方法及電子裝置

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DD267335B1 (de) 1987-12-24 1993-01-14 Univ Dresden Tech Schaltungsanordnung zur analyse eines elektroenzephalogramms
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Also Published As

Publication number Publication date
US20090221929A1 (en) 2009-09-03
DE112006002659A5 (de) 2008-07-10
WO2007014558A3 (fr) 2007-10-11
WO2007014558A2 (fr) 2007-02-08

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