Cerebral biopotential analysis system and method

• US 5,320,109 A
• Filed: 10/25/1991
• Issued: 06/14/1994
• Est. Priority Date: 10/25/1991
• Status: Expired due to Term

• Current Assignee: Nellcor Puritan Bennett LLC (Medtronic Plc)
• Original Assignee: Aspect Medical Systems, Inc. (Medtronic Plc)
• Inventors: Chiang, Hsing H., Mead, Peter A., Saini, Vikas, Chamoun, Nassib G.
• Primary Examiner(s): Kamm, William E.
• Assistant Examiner(s): MANUEL, GEORGE C
• Application Number:
  US07/782,636
• Time in Patent Office: 963 Days
• Field of Search: 128/731, 128/732, 128/733, 128/419 R, 364/413.02
• 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 5/374 Detecting the frequency distribution of signals, e.g. detecting delta, theta, alpha, beta or gamma waves
• CPC Class Codes: A61B 5/4821 Determining level or depth of anaesthesia A61B5/1106 takes precedence
• CPC Class Codes: A61B 5/725 using specific filters therefor, e.g. Kalman or adaptive filters A61B5/316 take precedence
• CPC Class Codes: A61B 5/7253 characterised by using transforms
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof

Abstract

Disclosed is a real time diagnostic apparatus and method quantitatively evaluating, in a noninvasive manner, cerebral phenomena. Surface electroencephalographic (EEG) signals are obtained and filtered in a desired frequency range. Digital EEG data is normalized and the dynamic phase and density relations within the signal are characterized by processing the filtered signals to generate Kth-ordered spectral values where K is an integer greater than 2. A diagnostic index which quantifies the detected cerebral phenomena is then derived from the generated Kth-order spectral values.

Claims

1. A method of noninvasively detecting cerebral phenomena comprising the steps of:

acquiring electroencephalographic signals through at least one electrode from a body surface of a subject being analyzed;

band pass filtering said electroencephalographic signals to obtain filtered signals in a desired frequency range;

dividing said filtered signals into a plurality of data records;

characterizing dynamic phase relations within said filtered signals by processing said filtered signals to generate Kth-order spectral values, where K is an integer greater than 2;

deriving from said generated Kth-order spectral values, a diagnostic index that quantifies the detected cerebral phenomena.

2. The method of noninvasively detecting cerebral phenomena of claim 1 wherein the step of acquiring electroencephalographic signals further comprises the step of attaching electrodes to a head of the subject being analyzed in order to obtain a unipolar electroencephalographic signal from each region of interest of both left and right hemispheres of the subject'"'"'s brain to which said electrodes are attached.

3. The method of noninvasively detecting cerebral phenomena of claim 1 wherein said Kth-order spectral values generated in said step of characterizing said dynamic phase relations are auto Kth-order spectral density values.

4. The method of noninvasively detecting cerebral phenomena of claim 1 wherein said Kth-order spectral values generated in said step of characterizing said dynamic phase relations are auto Kth-order coherence values.

5. The method of noninvasively detecting cerebral phenomena of claim 1 wherein said Kth-order spectral values generated in said step of characterizing said dynamic phase relations are auto Kth-order phase values.

6. The method of noninvasively detecting cerebral phenomena of claim 1 wherein said step of acquiring electroencephalographic signals further comprises the step of attaching electrodes to the head of the subject being analyzed in order to obtain bipolar data sets of electroencephalographic signals from left and right hemispheres of the subject'"'"'s brain to which said electrodes are attached.

7. The method of noninvasively detecting cerebral phenomena of claim 6 wherein one bipolar data set is acquired from a n frontal left hemisphere of the subject'"'"'s brain and another bipolar data set is acquired from a frontal right hemisphere of the subject'"'"'s brain.

8. The method of noninvasively detecting cerebral phenomena of claim 6 wherein one bipolar data set is acquired from a left occipital region of the subject'"'"'s brain and another bipolar data set is acquired from a right occipital region of the subject'"'"'s brain.

9. The method of noninvasively detecting cerebral phenomena of claim 6 wherein one bipolar data set is acquired from a left parietal region of the subject'"'"'s brain and another bipolar data set is acquired from a right parietal region of the subject'"'"'s brain.

10. The method of noninvasively detecting cerebral phenomena of claim 1 wherein said Kth-order spectral values generated in said step of characterizing said dynamic phase relations are cross Kth-order spectral density values.

11. The method of noninvasively detecting cerebral phenomena of claim 1 wherein said Kth-order spectral values generated in said step of characterizing said dynamic phase relations are cross Kth-order coherence values.

12. The method of noninvasively detecting cerebral phenomena of claim 1 wherein said Kth-order spectral values are generated in said step of characterizing said dynamic phase relations are cross Kth-order phase values.

13. The method of noninvasively detecting cerebral phenomena of claim 1 wherein the cerebral phenomena being detected are pain responses during surgical stress in the subject being analyzed.

14. The method of noninvasively detecting cerebral phenomena of claim 1 wherein the physical phenomenon being detected is the degree of cerebral intoxication of the subject being analyzed.

15. The method of noninvasively detecting cerebral phenomena of claim 1 wherein the cerebral phenomena being detected are normal or abnormal cognitive processes of a subject being analyzed.

16. The method of noninvasively detecting cerebral phenomena of claim 1 wherein the cerebral phenomenon being detected is chronic ischemia or infarction in the subject being analyzed.

17. The method of noninvasively detecting cerebral phenomena of claim 1 wherein the cerebral phenomenon being detected are cognitive processes caused by neurological disorders.

18. The method of noninvasively detecting cerebral phenomena of claim 1 wherein the cerebral phenomenon being detected are altered evoked potential responses.

19. The method of noninvasively detecting cerebral phenomena of claim 18 wherein said step of acquiring electorencephalographic signals comprises acquiring electorencephalographic signals through at least one electrode placed near areas of the brain in which the evoked potential response occurs.

20. The method of noninvasively detecting cerebral phenomena of claim 18 wherein said step of acquiring electorencephalographic signals comprises acquiring electorencephalographic signals from one complete evoked potential response.

21. The method of noninvasively detecting cerebral phenomena of claim 1 wherein said Kth-order spectral values generated in said step of characterizing said dynamic phase relations are average auto Kth-order complex product values.

22. The method of noninvasively detecting cerebral phenomena of claim 1 wherein said Kth-order spectral values generated in said step of characterizing said dynamic phase relations are average cross Kth-order real product values.

23. The method of noninvasively detecting cerebral phenomena of claim 1 wherein said Kth-order spectral values generated in said step of characterizing said dynamic phase relations are average cross Kth-order complex product values.

24. The method of noninvasively detecting cerebral phenomena of claim 1 wherein said Kth-order spectral values generated in said step of characterizing said dynamic phase relations are average auto Kth-order real product values.

25. A system for noninvasively detecting cerebral phenomena comprising:

means for acquiring electroencephalographic signals through at least one electrode from a body surface of a subject being analyzed;

means for band pass filtering said electroencephalographic signals to eliminate those signals outside a desired frequency range;

means for dividing said filtered signals into a plurality of data records;

means for generating Kth-order spectral values capable of characterizing dynamic phase relations within said filtered electroencephalographic signals where K is an integer greater than 2;

means for deriving a diagnostic index that quantifies the detected cerebral phenomena.

26. The system for noninvasively detecting cerebral phenomena of claim 25 further comprising a plurality of said means for acquiring electroencephalographic signals, each of said means for acquiring electroencephalographic signals being connected to said means for filtering.

27. The system for noninvasively detecting cerebral phenomena of claim 26 wherein said plurality of said means for acquiring electroencephalographic signals is a plurality of electrodes attachable to a head of a subject being analyzed to obtain a unipolar electroencephalographic signal from each of a plurality of regions of interest on both left and right hemispheres of the subject'"'"'s brain.

28. The system for noninvasively detecting cerebral phenomena of claim 25 wherein said means for acquiring electroencephalographic signals comprises:

a plurality of surface electrodes for mounting on a surface of a head of the subject being analyzed;

means for providing defibrillator protection for limiting voltage to said amplifier during a discharge;

means for amplifying said filtered signals for a high gain in order to maximize the dynamic range for high frequency, low energy wave components of said filtered signals;

means for feeding said signals to an analog-to-digital converter to convert said signals to digital signals.

29. The system for noninvasively detecting cerebral phenomena of claim 25 wherein said Kth-order spectral values are auto Kth-order spectral density values and further comprising means for organizing said auto Kth-order spectral density values in at least one array of auto Kth-order spectral density values.

30. The system for noninvasively detecting cerebral phenomena of claim 25 wherein said means for acquiring electroencephalographic signals from different regions of a brain of said subject.

31. The system for noninvasively detecting cerebral phenomena of claim 25 wherein said means for generating Kth-order spectral values comprises means for computing auto Kth-order phase values.

32. The system of noninvasively detecting cerebral phenomena of claim 25 wherein said means for generating Kth-order spectral values comprises means for computing auto Kth-order coherence values.

33. The system for noninvasively detecting cerebral phenomena of claim 25 wherein said means for generating Kth-order spectral values comprises means for computing an average auto Kth-order real product.

34. The system for noninvasively detecting cerebral phenomena of claim 25 wherein said means for generating Kth-order spectral values comprises means for computing an average auto Kth-order complex product.

35. The system for noninvasively detecting cerebral phenomena of claim 25 wherein said means for generating Kth-order spectral values comprises means for computing cross Kth-order spectral density values.

36. The system for noninvasively detecting cerebral phenomena of claim 25 wherein said means for generating Kth-order spectral values comprises means for computing cross Kth-order coherence values.

37. The system for noninvasively detecting cerebral phenomena of claim 25 wherein said means for generating Kth-order spectral values comprises means for computing cross Kth-order phase values.

38. The system for noninvasively detecting cerebral phenomena of claim 25 wherein said means for generating Kth-order spectral values comprises means for computing an average cross Kth-order real product.

39. The system for noninvasively detecting cerebral phenomena of claim 25 wherein said means for generating Kth-order spectral values comprises means for computing an average cross Kth-order complex product.

40. A method of generating a diagnostic index for quantifying the presence or absence of a phenomena which is represented by spectral values generated from acquired electrical signals of the phenomena, said method comprising the steps of:

sorting said spectral values into predetermined bins of ranges of spectral values;

summing all of the spectral values in each bin;

multiplying the sum of spectral values in each bin by a predetermined coefficient to obtain a bin product;

summing said bin products to obtain a diagnostic index which represents a degree of presence or absence of said phenomena.

41. The method of generating a diagnostic index of claim 40 wherein said acquired electrical signals are electroencephalographic signals.

42. A system for generating a diagnostic index for quantifying the presence or absence of a phenomena which is represented by spectral values generated from acquired electrical signals of the phenomena, said system comprising:

means for sorting said spectral values into predetermined bins of ranges of spectral values;

means for summing all of the spectral values in each bin;

means for multiplying the sum of spectral values in each bin by a predetermined coefficient to obtain a bin product;

means for summing said bin products to obtain a diagnostic index which represents a degree of presence or absence of said phenomena.

43. The system for generating a diagnostic index of claim 42 wherein said acquired electrical signals are electroencephalographic signals.

44. A method of noninvasively detecting cerebral phenomena comprising the steps of:

acquiring electroencephalographic signals through at least one electrode from a body surface of a subject being analyzed;

band pass filtering said electroencephalographic signals to obtain filtered signals in a desired frequency range;

dividing said filtered signals into a plurality of data records;

characterizing dynamic phase relations within said filtered signals by processing said filtered signals to generate third-order moment values;

deriving from said generated third-order moment values, a diagnostic index that quantifies the detected cerebral phenomena.

45. A system for noninvasively detecting cerebral phenomena comprising:

means for acquiring electroencephalographic signals through at least one electrode from a body surface of a subject being analyzed;

means for band pass filtering said electroencephalographic signals to eliminate those signals outside a desired frequency range;

means for dividing said filtered signals into a plurality of data records;

means for generating third-order moment values capable of characterizing dynamic phase relations within said filtered electroencephalographic signals;

means for deriving a diagnostic index that quantifies the detected cerebral phenomena.