Single Trial Detection in Encephalography

• US 20110144522A1
• Filed: 10/05/2010
• Published: 06/16/2011
• Est. Priority Date: 05/03/2002
• Status: Active Grant

• Current Assignee: Trustees Of Columbia University In The City Of New York (Columbia University)
• Original Assignee: Trustees Of Columbia University In The City Of New York (Columbia University)
• Inventors: Sajda, Paul, Parra, Lucas Cristobal
• Granted Patent: US 8,731,650 B2
• Time in Patent Office: Days
• US Class Current: 600/544
• CPC Class Codes: A61B 5/291 for electroencephalography [EEG]
• CPC Class Codes: A61B 5/374 Detecting the frequency distribution of signals, e.g. detecting delta, theta, alpha, beta or gamma waves
• CPC Class Codes: A61B 5/375 using biofeedback
• CPC Class Codes: G06F 2218/22 Source localisation; Inverse modelling

Abstract

An EEG cap (8) having 64 or 128 electrodes (10) is placed on the head of the subject (11) who is viewing CRT monitor (14). The signals on each channel are amplified by amplifier (17) and sent to an analog-to-digital converter (20). PC (23) captures and records the amplified signals and the signals are processed by signal processing PC (26) performing linear signal processing. The resulting signal is sent back to a feedback/display PC (29) having monitor (14).

Claims

1. A method for interpreting brain activity monitored by an array of brain activity sensors applied to the head of a subject, wherein each of the sensors are adapted to generate a response signal upon prompting of the subject by an external stimulus, comprising:

receiving two or more response signals from the array of brain activity sensors, each response signal corresponding to a different brain activity sensors;

determining two or more spatial weighting coefficients, each corresponding to one of the two or more response signals;

weighting each of the two or more received response signals in accordance with a corresponding one of the determined weighting coefficients; and

generating an output from the weighted two or more response signals, the output having a correlation to the brain activity of the subject in response to the external stimulus.

2. The method of claim 1, wherein the determining two or more spatial weighting coefficients comprises applying a linear classifier to each of the two or more response signals.

3. The method of claim 1, wherein the generating the output signal comprises linearly integrating the two or more weighted response signals.

4. The method of claim 1, wherein the correlation comprises a relatively high correlation.

5. The method of claim 3, wherein the linear integration comprises summation.

6. The method of claim 1, wherein the determining of two or more weighting coefficients comprises determining two or more weighting coefficients such that the weighted responses are maximally discriminating between first and second predetermined times corresponding to two stimuli where a maximum difference in brain activity is expected.

7. The method of claim 1, wherein the external stimulus comprises a visual stimulus.

8. The method of claim 1 further comprising:

identifying an expected scalp locality for discriminating components of the output signal relative to the external stimulus;

determining a sensor projection for each of the plurality of brain activity sensors;

using the determined sensor projections to identify the scalp locality for the actual discriminating components for the external stimulus; and

evaluating the validity of the output signal by determining whether the identified locality for the actual discriminating components is substantially the same as the expected locality.

9. A system for interpreting brain activity monitored by an array of brain activity sensors applied to the head of a subject, wherein each of the sensors are adapted to generate a response signal upon prompting of the subject by an external stimulus, comprising:

an input adapted to receive two or more response signals generated by at least a portion of the brain activity sensors, each response signal corresponding to a different brain activity sensors;

a data processor, coupled to the input, programmed to;

receive the two or more response signals from the input;

determine two or more spatial weighting coefficients, each corresponding to one of the two or more response signals;

weigh each of the two or more received response signals in accordance with a corresponding one of the computed weighting coefficients; and

generate an output from the weighted two or more response signals, the output having a correlation to the brain activity of the subject in response to the external stimulus.

10. The system of claim 9, wherein the data processor is further programmed such that the determining two or more spatial weighting coefficients comprises applying a linear classifier to each of the two or more response signals.

11. The system of claim 9, wherein the data processor is further programmed such that the output signal comprises linearly integrating the two or more weighted response signals.

12. The system of claim 9, wherein the correlation comprises a relatively high correlation.

13. The system of claim 11, wherein the linear integration comprises summation.

14. The system of claim 9, further comprising a feedback display coupled to the data processor.

15. The system of claim 14, wherein the feedback display comprises a display adapted to provide the external stimulus.

16. The system of claim 9, wherein the data processor is further programmed such that the determining of two or more weighting coefficients comprises determining two or more weighting coefficients such that the weighted responses are maximally discriminating between first and second predetermined times corresponding to two stimuli where a maximum difference in brain activity is expected.

17. The system of claim 9, wherein the brain activity sensors comprise EEG sensors.

18. The system of claim 9, wherein the brain activity sensors comprise MEG sensors.