Method and Device for Probabilistic Objective Assessment of Brain Function

• US 20100191139A1
• Filed: 01/28/2009
• Published: 07/29/2010
• Est. Priority Date: 01/28/2009
• Status: Active Grant

• Current Assignee: Brainscope SPV LLC
• Original Assignee: Brainscope Company Inc.
• Inventors: Causevic, Elvir, Jacquin, Arnaud
• Granted Patent: US 8,364,254 B2
• Time in Patent Office: Days
• US Class Current: 600/544
• CPC Class Codes: A61B 5/16 Devices for psychotechnics using teaching or educational appliances G09B1/00 - G09B7/00; Testing reaction times ; Devices for evaluating the psychological state
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/377 using evoked responses
• CPC Class Codes: A61B 5/4076 Diagnosing or monitoring particular conditions of the nervous system A61B5/4821, A61B5/4824 take precedence
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7207 of noise induced by motion artifacts
• CPC Class Codes: A61B 5/726 using Wavelet 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: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

A method and apparatus for providing objective assessment of the brain state of a subject using a field portable device. The method includes placing an electrode set coupled to a handheld base unit on the subject'"'"'s head, acquiring electrical brain signals from the subject through the electrode set, processing the acquired electrical brain signals using a feature extraction algorithm, classifying the extracted features into brain states, computing brain abnormality indices reflecting the probability of correct classification of brain state, and graphically displaying the classification result and the abnormality indices on the handheld base unit.

Claims

1. A method of assessing brain state of a subject comprising the steps of:

acquiring electrical signals from the brain using at least one electrode channel;

extracting quantitative features from the acquired signals;

classifying the extracted features into one or more brain states; and

computing a probabilistic index indicating the accuracy of the classification.

2. The method of claim 1, wherein multiple probabilistic indices corresponding to different classification tasks are computed.

3. The method of claim 2, wherein the multiple probabilistic indices are reported as a multidimensional vector.

4. The method of claim 2, wherein the step of classifying the extracted features is performed using a reference database.

5. The method of claim 4, wherein the reference database comprises of electrical brain activity signals/data from a plurality of individuals in the presence or absence of brain abnormalities.

6. The method of claim 4, further comprising the step of deriving an index map by graphically plotting the probabilistic indices generated from the brain electrical activity data in the reference database.

7. The method of claim 6, further comprising the step of modifying a decision boundary in the index map by incorporating new data into the map.

8. The method of claim 7, wherein the multidimensional vector is plotted on the index map.

9. The method of claim 1, wherein the index computed is a Brain Abnormality Index (BAI) indicating the accuracy of a normal vs. abnormal classification.

10. The method of claim 1, wherein the index computed is a Brain Focality Index (BFI) indicating the accuracy of a focal vs. diffused classification.

11. The method of claim 1, wherein the electrical signals from the brain comprises spontaneous electrical activity.

12. The method of claim 1, wherein the electrical signals from the brain comprises evoked potentials.

13. The method of claim 1, wherein the electrical signals from the brain comprises spontaneous electrical activity and evoked potentials.

14. The method of claim 1, wherein the step of feature extraction is performed using diffusion geometric analysis.

15. The method of claim 1, wherein the step of feature extraction is performed using wavelet packet transformation.

16. The method of claim 1, wherein the step of feature extraction is performed using Fast Fourier Transformation.

17. The method of claim 1, wherein the classification is performed using a binary classifier.

18. The method of claim 17, wherein the classifier is a linear discriminant function classifier.

19. The method of claim 18, wherein the probabilistic index is computed from the discriminant classification score.

20. The method of claim 19, further comprising the step of plotting Receiver Operating Characteristic (ROC) curves.

21. The method of claim 1, wherein the assessment of brain state is performed using a portable, handheld device.

22. An apparatus for assessing the brain state of a subject, comprising:

a headset comprising at least one electrode for acquiring brain electrical signals;

a base unit;

wherein

the base unit comprises a processor configured to utilize one or more operating instructions stored in a memory to perform feature extraction from the brain electrical signals, classify the extracted signal features into one or more brain states, and compute probabilistic indices of the classification accuracy.

23. The apparatus of claim 22, wherein the processor is configured to output an objective assessment of the brain state of the subject.

24. The apparatus of claim 23, wherein the processor is configured to output the probabilistic indices.

25. The apparatus of claim 22, further comprising a display wherein a result of one or more operations performed by the processor is displayed.

26. The apparatus of claim 25, wherein the probabilistic indices are reported on the display as horizontal index bars.

27. The apparatus of claim 25, wherein the probabilistic indices are reported on the display as a multidimensional vector.

28. The apparatus of claim 27, wherein an index map generated from the probabilistic indices is reported on the display.

29. The apparatus of claim 28, wherein the multidimensional vector is superimposed on the index map.

30. The apparatus of claim 28, wherein the index map is stored in the memory.

31. The apparatus of claim 28, wherein the index map is partitioned into multiple regions corresponding to different brain states.

32. The apparatus of claim 30, wherein the processor is configured to accept instructions from a user to modify a decision boundary corresponding to a brain state on the index map.