Method for assessing brain function and portable automatic brain function assessment apparatus

• US 20070032737A1
• Filed: 08/02/2005
• Published: 02/08/2007
• Est. Priority Date: 08/02/2005
• Status: Active Grant

• Current Assignee: Brainscope SPV LLC
• Original Assignee: Brainscope Company Inc.
• Inventors: Causevic, Elvir, Combs, Arthur
• Granted Patent: US 7,904,144 B2
• Time in Patent Office: Days
• US Class Current: 600/544
• 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 5/377 using evoked responses
• CPC Class Codes: A61B 5/411 Detecting or monitoring allergy or intolerance reactions to an allergenic agent or substance
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• 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 performing rapid brain assessment may provide emergency triage to head trauma patients by analyzing a combination of spontaneous and evoked brain potentials. The spontaneous and evoked potentials are analyzed, and the results classified, to present a real-time assessment of a patient'"'"'s brain, diagnosing any potential abnormalities therein.

Claims

1. A method of determining a neurological state of a subject comprising the steps of:

acquiring spontaneous signals through an electrode set;

processing the acquired signals;

extracting desired features from the processed signals; and

classifying the extracted features into one or more diagnostic categories.

2. A method of determining a neurological state of a subject comprising the steps of:

evoking brain response signals using audio, visual, electrical, or other stimulus means;

acquiring the evoked signals through an electrode set;

processing the acquired signals;

extracting desired features from the processed signals; and

classifying the extracted features.

3. A method of determining a neurological state of a subject comprising the steps of:

acquiring spontaneous and evoked signals through the electrode set;

processing the acquired signals;

extracting desired features from the processed signals; and

classifying the extracted features.

4. The method according to claim 3, wherein

the electrode set comprises less than 19 electrodes.

5. The method according to claim 3, wherein the spontaneous signals comprise:

electroencephalographic (EEG) signals.

6. The method according to claim 3, wherein the evoked signals comprise:

auditory evoked potentials (AEP).

7. The method according to claim 6, wherein the auditory evoked potentials comprise at least one of:

auditory brainstem response (ABR) potentials, auditory mid-latency response (AMLR) potentials, or auditory late response (ALR) potentials, including P100 responses and P300 responses.

8. The method according to claim 3, wherein the step of processing the signals comprises:

de-noising the acquired signals using at least one wavelet packet de-noising algorithm.

9. The method of according to claim 3, wherein the step of processing the signals comprises:

removing artifacts from the acquired signal.

10. The method according to claim 9, wherein removing artifacts comprises:

removing artifact sections of the acquired signal.

11. The method according to claim 9, wherein removing artifacts comprises:

subtracting artifacts from the acquired signal.

12. The method according to claim 8, wherein the step of processing the signals further comprises:

filtering the signals using a dual-tree complex wavelet transform of the acquired signals.

13. The method according to claim 3, wherein the step of extracting features comprises:

performing spectral analysis and statistical procedures on the processed signals, and extracting features.

14. The method according to claim 3, wherein the step of extracting features comprises:

performing wavelet packet analysis on the processed signals to extract features.

15. The method according to claim 3, wherein the step of extracting features comprises:

performing diffusion geometric analysis on the processed signals to extract features.

16. The method according to claim 3, wherein the step of extracting features comprises:

performing microstate analysis on the processed signals, to extract features.

17. The method according to claim 10, wherein applying spectral analysis comprises:

applying a Fast Fourier Transform (FFT) to the processed signals, dividing the signals into frequency bands.

18. The method according to claim 11, wherein

the extracted features include absolute and relative power, symmetry and coherence.

19. The method according to claim 3, wherein the step of extracting features comprises:

applying wavelet-packet local discriminant basis algorithms.

20. The method according to claim 3, wherein the step of classifying comprises:

applying discriminant analysis to the extracted features to classify the extracted features into one or more diagnostic categories.

21. The method according to claim 3, wherein the step of classifying comprises:

applying wavelet-packets to the extracted features to classify the subject into one or more diagnostic categories.

22. The method according to claim 3, further comprising the step of:

determining the neurological state of the subject based on the classification.

23. The method according to claim 22, wherein the step of determining further comprises:

determining if the neurological state is normal or abnormal.

24. The method according to claim 23, further comprising:

determining if an abnormal neurological state is psychiatric or “

functional”

in nature, organic in nature, or an emergency or “

Alert”

condition.

25. The method according to claim 24, wherein

neurological states that constitute an emergency condition include seizure, abnormal brainstem response, or burst suppression.

26. The method according to claim 23, further comprising:

determining if an abnormal neurological state that is organic in nature is global or lateral.

27. The method according to claim 3, further comprising:

graphically displaying the determination;

graphically displaying representations of the brain based on the determination;

storing data related to the determination.

28. An apparatus for the neurological state of a subject, comprising:

a processor;

a memory operatively coupled to the processor, wherein

the memory stores one or more operating instructions;

a multi-channel input-output interface operatively coupled to the processor, wherein

the multi-channel input-output interface is configured to receive external electrical signals through a set of electrodes placed on the subject; and

the processor is configured to utilize the one or more operating instructions to perform one or more operations on signals received from the multi-channel input-output interface.

29. The apparatus of claim 28, further comprising:

a display device, wherein

the display device is operatively connected to the processor and the processor is further configured to display results of the one or more operations on the display device.

30. The apparatus of claim 28, further comprising:

a bi-directional communications channel operatively connected to the multi-channel input-output interface and to the processor to communicate the received external signals.

31. The apparatus of claim 28, further comprising:

a low voltage multi-channel preamplifier operatively connected to the multi-channel input-output interface.

32. The apparatus of claim 31, wherein

the low voltage multi-channel preamplifier has a high noise tolerance.

33. The apparatus of claim 28, wherein the multi-channel input-output interface includes an electroencephalograph testing interface and an auditory evoked potentials testing interface;

and

wherein the processor is configured with the one or more stored operating instructions for auditory tests selected from the group comprising electroencephalograph test procedures, auditory evoked potentials test procedures, and combinations thereof.

34. The apparatus of claim 28, wherein

the processor has an internal memory, and the processor is configured to utilize the internal memory to execute one or more operating instructions for processing the received external signals.

35. The apparatus of claim 28, wherein the operating instructions include:

instructions for processing the external signals;

instructions for extracting features from the external signals;

instructions for classifying the subject based on extracted features; and

instructions for determining the neurological state of a subject based on the classification.

36. The apparatus of claim 35, wherein

the instructions for processing the external signals include instructions to filter the received external signals.

37. The apparatus of claim 36, wherein the filtering comprises:

using a dual-tree complex wavelet transform of the received external signals.

38. The apparatus of claim 28, wherein the set of electrodes comprises:

a plurality of electrodes placed on the subject'"'"'s forehead; and

at least one electrode placed in at least one of the ears of the subject.

39. The apparatus of claim 28, further comprising:

a stimulation device operatively connected to the multi-channel input-output interface for evoking an auditory potential in the subject.

40. The apparatus of claim 28, wherein

the apparatus is housed in a hand-held enclosure.

41. The apparatus of claim 28, wherein the multi-channel input-output interface further comprises:

a wireless multi-channel input-output interface.

42. A kit for performing an emergency neurological diagnosis of a patient suffering from an altered mental state, the kit including:

the apparatus of claim 28;

instructions for using the apparatus; and

a portable carrying case for the apparatus.

47. The triage apparatus of claim 40, wherein

the electrode set comprises less than 19 electrodes.

43. An apparatus for providing an automatic brain function assessment comprising;

an electrode set;

a processor;

wherein

the electrode set and the processor are operatively connected through a multi-channel input-output interface;

a display operatively connected to the processor;

a user interface operatively connected to the processor; and

internal memory, wherein

the memory contains instructions for providing a real-time assessment of a subject'"'"'s brain function; and

the memory contains instructions for processing signals acquired by the electrode set using wavelet-packet algorithms.

44. A method for providing a triage assessment of a patient'"'"'s brain function comprising the steps of:

measuring the spontaneous brain activity of the patient;

stimulating the patient and measuring the evoked brain activity therefrom;

processing the spontaneous and evoked brain activity, wherein

the processing is performed in real-time using wavelet-packet algorithms;

providing a triage assessment of the patient based on the processed brain activity.

45. The method according to claim 44, wherein

the steps of processing and providing an assessment are performed by a portable hand-held device.

46. A triage apparatus comprising:

an electrode set;

an amplifier operatively connected to the electrode set;

a processor operatively connected to the amplifier, wherein

the processor is configured to process external signals acquired by the electrode set using wavelets.

48. A neurological triage apparatus comprising:

a processor configured to process acquired spontaneous and evoked signals using wavelets.

49. An apparatus for performing brain assessment, comprising:

a handheld portable apparatus weighing less than about 600 g.