Automated realtime interpretation of brain waves

• US 20040077967A1
• Filed: 08/12/2003
• Published: 04/22/2004
• Est. Priority Date: 02/13/2001
• Status: Active Grant

• Current Assignee: Jordan Neuroscience Inc.
• Original Assignee: Jordan Neuroscience Inc.
• Inventors: Jordan, Kenneth George
• Granted Patent: US 6,985,769 B2
• Time in Patent Office: Days
• US Class Current: 600/544
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• 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 5/4076 Diagnosing or monitoring particular conditions of the nervous system A61B5/4821, A61B5/4824 take precedence
• CPC Class Codes: A61B 5/4094 Diagnosing or monitoring seizure diseases, e.g. epilepsy
• 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

Abstract

A method and system for automated real time interpretation of brain waves in an acute brain injury of a patient using correlations between brain wave frequency power ratio and wave morphology, determined by a measure of the rhythmicity and variability of the brain wave as a function of the slope of the brain wave upstroke, the arc of the brain wave, and the synchronicity of the brain wave. A system is provided with a central processing unit (16), an electroencephalogram acquisition unit (18), a reference database (24), a quantitative electroencephalogram analysis program (14), and a display device (26) for communicating the classification of the acquired electroencephalographic signals. Artifact rejection is also provided.

Claims

1. (cancelled)

2. (Amended) A method for automated real time interpretation of brain waves in an acute brain injury of a patient, comprising a correlation between brain wave frequency power ratio and wave morphology, wherein the power ratio is an alpha-beta/theta-delta power ratio.

3. (Amended) A method for automated real time interpretation of brain waves in an acute brain injury of a patient, comprising a correlation between brain wave frequency power ratio and wave morphology, wherein wave morphology is determined by a measure of the rhythmicity and variability of the brain wave, as a function of the slope of the brain wave upstroke, the area of the brain wave, and the synchronicity of the brain wave.

4. A method for automated real time interpretation of brain waves in an acute brain injury of a patient, comprising the steps of:

a) acquiring electroencephalographic signals from the patient;

b) selecting one or more than one of the acquired electroencephalographic signal for analysis;

d) transforming the one or more than one selected electroencephalographic signal into one or more than one frequency component;

e) calculating a power ratio for each of the one or more than one selected electroencephalographic signal;

f) accessing a reference database storing reference power ratios calculated from normal brain wave activity data;

g) comparing the one or more than one calculated power ratio to the reference power ratios to determine whether the one or more than one calculated power ratio is abnormally high or low;

h) interpreting the one or more than one selected electroencephalographic signal based upon the comparison of the one or more than one calculated power ratio to the reference power ratios; and

i) communicating the interpretation of the selected electroencephalographic signals as the interpretation of the acquired electroencephalographic signals.

5. The method of claim 4, wherein the power ratio is an alpha-beta/theta-delta power ratio.

6. The method of claim 4 further comprising the step of measuring the wave morphology of the one or more than one selected electroencephalographic signal, and wherein the interpreting step further comprises consideration of the measured wave morphology.

7. The method of claim 6, wherein the power ratio is an alpha-beta/theta-delta power ratio.

8. The method of claim 6, wherein wave morphology is determined by a measure of the rhytimicity and variability of the brain wave, as a function of the slope of the brain wave upstroke, the area of the brain wave, and the synchronicity of the brain wave.

9. The method of claim 4, wherein the reference database further comprises classification data correlating acute brain injury electroencephalographic categories with specific types of brain dysfunction, the method further comprises the step of classifying the one or more than one compared power ratio into one or more than one of the acute brain injury electroencephalographic categories, and the communicating step further comprises communicating the classification.

10. The method of claim 4 wherein the step of comparing further comprises determining the spatial distribution of any abnormality.

11. The method of claim 4 wherein the communicating step further comprises displaying a quadrant schematic representation for communicating the interpretation of the electroencephalographic signals.

12. A method for automated real time interpretation of brain waves in an acute brain injury of a patient, comprising the steps of, under the control of a user system:

a) connecting one or more than one electroencephalogram needle electrode of an electroencephalogram acquisition unit to the patient;

b) activating the electroencephalogram acquisition unit and transmitting digital electroencephalographic signals from the patient to the electroencephalogram acquisition unit; and

c) receiving a display of the electroencephalogram of the patient connected to the electroencephalogram acquisition unit and information automatically interpreting the meaning of the display.

13. The method of claim 12 wherein the receiving step further comprises receiving a display illustrating a quadrant schematic representation of the interpretation of the electroencephalographic signals.

14. The method of claim 12, further comprising the step of receiving information displaying the position of one or more than one electroencephalogram needle electrode connected to the patient.

15. The method of claim 14, further comprising the step of receiving a request to alter the position of one or more than one electroencephalogram needle electrode connected to the patient.

16. The method of claim 12, further comprising the step of requesting demographic data relating to the connected patient.

17. The method of claim 12, further comprising the step of requesting clinical information about the connected patient'"'"'s condition, medications, and other relevant medical information required for clinical correlation of electroencephalogram data.

18. The method of claim 12, further comprising the step of scanning bar-coded data having information regarding the patient connected to the electroencephalogram acquisition unit.

19. A system for automated real time interpretation of brain waves in acute brain injuries in a patient, comprising:

a) a central processing unit;

b) an electroencephalogram acquisition unit coupled to the central processing unit having a first port for receiving electroencephalographic signals;

c) a reference database coupled to the central processing unit for storing one or more than one reference power ratio calculated from normal brain wave activity;

d) a first memory coupled to the central processing unit for storing a quantitative electroencephalogram analysis program, the quantitative electroencephalogram analysis program comprising;

a transform module for transforming acquired electroencephalographic signals into frequency components;

a calculation module for calculating a power ratio from the frequency components;

a classification module for comparing the calculated power ratio to reference data and classifying the acquired electroencephalographic signals; and

e) a display device for communicating the classification of the acquired electroencephalographic signals.

20. The system of claim 19 wherein the reference database further comprises classification data correlating acute brain injury electroencephalographic categories with specific types of brain dysfunction, the classification module is further for classifying the calculated power ratio into one or more than one of the acute brain injury electroencephalographic categories, and the display device is further for communicating the classification.

21. The system of claim 19, wherein the calculated power ratio is an alpha-beta/theta-delta power ratio.

22. The system of claim 19, wherein the classification module is an artificial neural network.

23. The system of claim 19, further comprising a second memory coupled to the central processing unit for storing an artifact pattern recognition program for minimizing artifact contamination of received digital electroencephalographic signals.

24. The system of claim 19, wherein the calculation module is further for calculating rhythmicity and variability of the brain wave, as a function of the slope of the brain wave upstroke, the area of the brain wave, and the synchronicity of the brain wave.

25. A system for automated real time interpretation of brain waves in acute brain injuries in a patient, comprising:

a) means for central processing unit;

b) means for receiving electroencephalographic signals from the patient;

c) means for storing one or more than one reference power ratio calculated from normal brain wave activity;

d) means for storing a quantitative electroencephalogram analysis program, the quantitative electroencephalogram analysis program comprising;

means for transforming acquired electroencephalographic signals into frequency components;

means for calculating a power ratio from the frequency components;

means for comparing the calculated power ratio to reference data and classifying the acquired electroencephalographic signals; and

e) means for communicating the classification of the acquired electroencephalographic signals.