Method and device for evaluating an EEG carried out in the context of anaesthesia or intensive care

• US 6,011,990 A
• Filed: 04/17/1998
• Issued: 01/04/2000
• Est. Priority Date: 10/19/1995
• Status: Expired due to Term

• Current Assignee: Arthur Schultz
• Original Assignee: Arthur Schultz
• Inventors: Schultz, Barbara, Schultz, Arthur
• Primary Examiner(s): Kamm, William E.
• Application Number:
  US09/051,905
• Time in Patent Office: 627 Days
• Field of Search: 600/544
• US Class Current: 600/544
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/372 Analysis of electroencephalograms
• CPC Class Codes: A61B 5/384 Recording apparatus or displays specially adapted therefor
• CPC Class Codes: A61B 5/4821 Determining level or depth of anaesthesia A61B5/1106 takes precedence
• CPC Class Codes: A61B 5/721 using a separate sensor to detect motion or using motion information derived from signals other than the physiological signal to be measured
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7267 involving training the classification device
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

A method of evaluating an EEG carried out in the context of anaesthesia or intensive care is disclosed. To this end, parameters from the time and/or frequency domains are determined from the EEG curves, the parameters determined are used in multivariate classification functions, and on this basis the EEG carried out in the context of anaesthesia or intensive care is automatically divided into stages.

Claims

1. A method for evaluating an EEG of a person under anaesthesia or in intensive care comprising:

(a) measuring EEG curves of the person through a plurality of stages;

(b) determining time or frequency domain parameters from the measured EEG curves;

(c) inserting the determined parameters into multivariate classification functions;

(d) automatically allocating said functions into the stages of the EEG;

(e) determining limit values of the parameters, including EEG signal strength in relation to a base line and correcting the multivariate classification functions using the limit values;

(f) determining movement artifacts caused by movements during the EEG; and

(g) suppressing allocation into stages based on an evaluation of the movement artifacts.

2. A method according to claim 1 further comprising selecting age-specific classification functions for the person from age-dependent classification functions stored in a computer memory.

3. A method according to claim 1 further comprising selecting medication-specific classification functions from medication-dependent classification functions stored in a computer memory.

4. A method according to claim 1 further comprising determining muscle artifacts from the time or frequency domain parameters of the EEG curves and suppressing the allocation into stages based on an evaluation of the muscle artifacts.

5. A method according to claim 1 further comprising determining additional artifacts resulting from interference radiation from an electromedical apparatus and suppressing the allocation into stages based on an evaluation of the interference-radiation artifacts.

6. A device for evaluating an anaesthesia EEG or an intensive-care EEG of a person comprising

(a) a measuring device for measuring EEG curves of the person through a plurality of stages;

(b) a movement sensor having at least one sensor element adapted to be attached to or coupled with the head of the person for determining movement artifacts; and

(c) a computer coupled to the measuring device and the movement sensor, said computer comprising;

(i) means for determining time or frequency domain parameters from the measured EEG curves;

(ii) means for inserting the determined parameters into multivariate classification functions;

(iii) means for automatically allocating said functions into the stages of the EEG;

(iv) means for determining limit values of the parameters, including EEG signal strength in relation to a base line, and for undertaking a correction of the multivariate classification function using the limit values; and

(v) means for evaluating movement artifacts determined by the movement sensor in order to suppress the allocation into stages of the EEG.

7. A device according to claim 6 wherein the computer further comprises storage means for storing age-dependent classification functions and means for selecting age-specific classification functions from the stored classification functions by entering an age.

8. A device according to claim 6 wherein the computer further comprises storage means for storing medication-dependent classification functions and means for selecting classification functions specific to a medication used on the person from the stored classification functions by entering information about the medication.

9. A device according to claim 6 wherein the sensor element is an acceleration transducer or a displacement transducer.

10. A device according to claim 6 wherein the sensor element comprises electrical lines coupled to the head of the person, said lines being situated in a magnetic or electrical field and further comprising means for evaluating currents induced or voltages generated by said lines from movements in the field or changes in field strength.

11. A device according to claim 6 wherein the computer further comprises means for evaluating muscle artifacts from the time or frequency domain parameters of the EEG curves in order to suppress the allocation into stages of the EEG.

12. A device according to claim 6 further comprising an interference-radiation sensor coupled to the computer and wherein the computer further comprises means for evaluating interference radiation from an electromedical apparatus sensed by said interference-radiation sensor in order to suppress the allocation into stages of the EEG.