SENSORY-EVOKED POTENTIAL (SEP) CLASSIFICATION/DETECTION IN THE TIME DOMAIN

• US 20110040202A1
• Filed: 09/20/2010
• Published: 02/17/2011
• Est. Priority Date: 03/16/2009
• Status: Active Grant

• Current Assignee: Neurosky Incorporated
• Original Assignee: Neurosky Incorporated
• Inventors: Sullivan, Thomas J., Luo, An, Delorme, Arnaud
• Granted Patent: US 8,391,966 B2
• Time in Patent Office: Days
• US Class Current: 600/544
• CPC Class Codes: A61B 5/165 Evaluating the state of mind, e.g. depression, anxiety
• CPC Class Codes: A61B 5/18 for vehicle drivers or machine operators
• CPC Class Codes: A61B 5/372 Analysis of electroencephalograms
• CPC Class Codes: A61B 5/378 Visual stimuli
• CPC Class Codes: A61B 5/38 Acoustic or auditory stimuli
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• 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: G06F 3/015 Input arrangements based on nervous system activity detection, e.g. brain waves [EEG] detection, electromyograms [EMG] detection, electrodermal response detection
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Techniques are disclosed for sensory-evoked potential (SEPs, e.g., visual-evoked potentials) signal detection/classification by synchronizing EEG to the repeated presentation of sensory stimuli in the time domain. In some embodiments, a system receives a plurality of EEG signal samples, generates a stimulus-locked EEG and determines whether the plurality of EEG signal samples are evoked in response to a pattern of stimulus. In some embodiments, no prior knowledge about the update pattern (such as the flashing frequency of a visual stimulus) of the stimulus and no prior knowledge about an individual user'"'"'s EEG pattern are required.

Claims

1. A method for sensory-evoked potential signal classification, comprising:

receiving a plurality of electroencephalography signal samples;

generating a stimulus-locked electroencephalography signal sample; and

determining whether the plurality of electroencephalography signal samples are evoked in response to a pattern of stimulus.

2. The method recited in claim 1, wherein advanced training of a user'"'"'s electroencephalography pattern is not required.

3. The method recited in claim 1, wherein advanced knowledge of the stimulus pattern is not required.

4. The method recited in claim 1, wherein sensory-evoked potential signal classification is performed by synchronizing electroencephalography signal samples to repeated presentation of sensory stimuli in the time domain.

5. The method recited in claim 1, wherein sensory-evoked potential signal classification is performed by synchronizing electroencephalography signal samples to repeated presentation of sensory stimuli in the time domain, wherein the sensory-evoked potential signal classification includes visually evoked potentials.

6. The method recited in claim 1, further comprising:

detecting a plurality of electroencephalography signals.

7. The method recited in claim 1, further comprising:

recording the plurality of electroencephalography signal samples.

8. The method recited in claim 1, further comprising:

synchronizing the plurality of electroencephalography signal samples to the pattern of stimulus.

9. The method recited in claim 1, further comprising:

synchronizing each electroencephalography signal sample to an onset of the pattern of stimulus.

10. The method recited in claim 1, further comprising:

determining which stimulus is attend to by a user.

11. The method recited in claim 1, further comprising:

generating a control signal based on the sensory-evoked potential signal classification.

12. The method recited in claim 1, further comprising:

calculating a mutual relationship between pairs of segments for the stimulus-locked electroencephalography signal sample;

determining a statistical measure of the mutual relationship for each stimulus;

determining if a stimulus is being attend to by a user according to the statistic measure of the mutual relationship for each stimulus using a classifier.

13. The method recited in claim 1, further comprising:

calculating a mutual relationship between pairs of segments for the stimulus-locked electroencephalography signal sample;

determining a statistical measure of the mutual relationship for each stimulus;

determining if a stimulus is being attend to by a user according to the statistic measure of the mutual relationship for each stimulus using a classifier,

wherein the mutual relationship includes correlation, mutual information, or covariance.

14. The method recited in claim 1, further comprising:

calculating a mutual relationship between pairs of segments for the stimulus-locked electroencephalography signal sample;

determining a statistical measure of the mutual relationship for each stimulus;

determining if a stimulus is being attend to by a user according to the statistic measure of the mutual relationship for each stimulus using a classifier,

wherein the statistical measure includes a mean, a median value, or a sum.

15. A system for sensory-evoked potential signal classification, comprising:

a processor configured to;

receive a plurality of electroencephalography signal samples;

generate a stimulus-locked electroencephalography signal sample; and

determine whether the plurality of electroencephalography signal samples are evoked in response to a pattern of stimulus; and

a memory coupled to the processor and configured to provide the processor with instructions.

16. The system recited in claim 15, wherein advanced training of a user'"'"'s electroencephalography pattern is not required.

17. The system recited in claim 15, wherein advanced knowledge of the stimulus pattern is not required.

18. The system recited in claim 15, wherein sensory-evoked potential signal classification is performed by synchronizing electroencephalography signal samples to repeated presentation of sensory stimuli in the time domain, wherein the sensory-evoked potential signal classification includes visually evoked potentials.

19. A computer program product for sensory-evoked potential signal classification, the computer program product being embodied in a computer readable storage medium and comprising computer instructions for:

receive a plurality of electroencephalography signal samples;

generate a stimulus-locked electroencephalography signal sample; and

determine whether the plurality of electroencephalography signal samples are evoked in response to a pattern of stimulus.

20. The computer program product recited in claim 19, wherein advanced training of a user'"'"'s electroencephalography pattern is not required.

21. The computer program product recited in claim 19, wherein advanced knowledge of the stimulus pattern is not required.

22. The computer program product recited in claim 19, wherein sensory-evoked potential signal classification is performed by synchronizing electroencephalography signal samples to repeated presentation of sensory stimuli in the time domain, wherein the sensory-evoked potential signal classification includes visually evoked potentials.