System for the prediction, rapid detection, warning, prevention or control of changes in activity states in the brain of a subject

• US 6,549,804 B1
• Filed: 06/10/1999
• Issued: 04/15/2003
• Est. Priority Date: 01/23/1996
• Status: Expired due to Term

• Current Assignee: University of Kansas
• Original Assignee: University of Kansas
• Inventors: Frei, Mark, Lerner, David, Dorfmeister, Josef, Ralston, John, Osorio, Ivan
• Primary Examiner(s): Lateef, Marvin M.
• Assistant Examiner(s): MANTIS MERCADER, ELENI M
• Application Number:
  US09/329,593
• Time in Patent Office: 1,405 Days
• Field of Search: 600/544, 600/545, 600/546, 600/300, 607/45
• 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 5/4094 Diagnosing or monitoring seizure diseases, e.g. epilepsy
• CPC Class Codes: A61B 5/415 the glands, e.g. tonsils, adenoids or thymus
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A61B 5/726 using Wavelet transforms
• CPC Class Codes: A61N 1/36025 for treating a mental or cerebral condition
• CPC Class Codes: A61N 1/36064 Epilepsy
• CPC Class Codes: A61N 1/36135 using physiological parameters

Abstract

A system (10) analyzes signals representative of a subject'"'"'s brain activity in a signal processor (12) for information indicating the subject'"'"'s current activity state and for predicting a change in the activity state. One preferred embodiment uses a combination of nonlinear filtering methods to perform real-time analysis of the electro-encephalogram (EEG) or electro-corticogram (ECoG) signals from a subject patient for information indicative of or predictive of a seizure, and to complete the needed analysis at least before clinical seizure onset. The preferred system then performs an output task for prevention or abatement of the seizure, or for recording pertinent data.

Claims

1. A method of predicting or detecting the occurrence of abnormal activity in the brain of a subject, said method comprising the steps of:

(a) receiving into a signal processor input signals indicative of a subject'"'"'s brain activity;

(b) determining ictal components in said input signals by applying to said input signals a first filter configured to extract and enhance ictal components of said input signals;

(c) measuring ictal activity in a foreground epoch of said input signals by applying a first order-statistic filter to said ictal components corresponding to said foreground epoch to produce a foreground measure of said ictal activity;

(d) measuring ictal activity in a background epoch of said input signals by applying a second order-statistic filter to said ictal components corresponding to said background epoch to produce a background measure of said ictal activity, said background epoch occurring before said foreground epoch;

(e) determining whether a ratio of said foreground measure to said background measure reaches a threshold level, such being indicative of the occurrence of abnormal activity in the brain of a subject; and

(f) performing steps (a)-(e) while said abnormal activity is occurring before the onset of electroencephalographic waves of said abnormal activity.

2. The method as set forth in claim 1, step (d) including the further step of using time- and state-weighted averaging in determining said background measure of said ictal activity.

3. A method of predicting or detecting the occurrence of abnormal activity in the brain of a subject, said method comprising the steps of:

(a) receiving into a signal processor input signals indicative of a subject'"'"'s brain activity;

(b) selecting and applying at least one filter of a filter bank having a plurality of filters configured to extract ictal components of said input signals, wherein said at least one filter is selected as the filter of said filter bank that provides the greatest differentiation of ictal components from non-ictal components of said input signals;

(c) applying an order-statistic filter to said ictal components corresponding to a foreground epoch of said input signals to produce a foreground measure of said ictal activity;

(d) determining whether said foreground measure reaches a threshold level, such being indicative of the occurrence of said abnormal activity; and

(e) performing steps (a)-(d) while said abnormal activity is occurring before the onset of electroencephalographic waves of said abnormal activity.

4. A method of predicting or detecting the occurrence of abnormal activity in the brain of a subject, said method comprising the steps of:

(a) receiving into a signal processor input signals indicative of a subject'"'"'s brain activity;

(b) determining ictal components in said input signals by applying a filter configured to extract ictal components of said input signals, said filter further configured to increase differentiation of said ictal components from non-ictal components of said input signals;

(c) applying an order-statistic filter to said ictal components in a foreground epoch of said input signals to produce a foreground measure of ictal activity in said foreground epoch;

(d) determining whether said foreground measure reaches a threshold level, such being indicative of the occurrence of said abnormal activity; and

(e) performing steps (a)-(d) while said abnormal activity is occurring before the onset of electroencephalographic waves of said abnormal activity.

5. The method as set forth in claim 4, wherein said filter is selected from a group consisting of filters designed using random search algorithms, evolving algorithms, and genetic algorithms.

6. A method of predicting or detecting the occurrence of a seizure in the brain of a subject, said method comprising the steps of:

(a) receiving into a signal processor input signals indicative of a subject'"'"'s brain activity;

(b) analyzing said signals to detect at least one precursor predictive of the occurrence of a seizure in the subject; and

(c) upon occurrence of said at least one precursor, producing an output in response thereto before the onset of electroencephalographic waves signaling the occurrence of the seizure;

wherein step (b) includes the step of detecting spikes in said signals, each spike presenting a polarity;

determining the sharpness of each of said spikes by determining a parabola of optimal fit for each of said spikes;

determining an index of relative sharpness of each spike to that of other spikes by comparing said spike'"'"'s sharpness to the sharpness of other spikes in a selected time window;

determining whether said index reaches a predetermined level; and

determining whether said spikes reaching said predetermined level fit a predetermined pattern, such being predictive of a seizure.

7. A method of predicting or detecting the occurrence of abnormal activity in the brain of a subject, said method comprising the steps of:

(a) receiving into a signal processor input signals indicative of a subject'"'"'s brain activity;

(b) analyzing said signals to detect at least one precursor predictive of the occurrence of a seizure in the subject; and

(c) upon the occurrence of said at least one precursor, producing an output in response thereto before the onset of electroencephalographic waves signaling the occurrence of said abnormal activity;

wherein step (b) includes the step of detecting said precursor by determining a ratio of background signal energy in at least one frequency band compared to current signal energy in said at least one band and determining whether said ratio reaches a predetermined level, such being predictive of a seizure.

8. A method of predicting or detecting the occurrence of abnormal activity in the brain of a subject, said method comprising the steps of:

(a) receiving into a signal processor input signals indicative of a subject'"'"'s brain activity;

(b) analyzing said signals to detect at least one precursor predictive of the occurrence of a seizure in the subject; and

(c) upon the occurrence of said at least one precursor, producing an output in response thereto before the onset of electroencephalographic waves signaling the occurrence of said abnormal activity;

wherein step (b) includes the step of detecting epileptiform waves in said input signals, said waves having a characteristic shape, amplitude, pattern or temporal spatial probability distribution predictive of the abnormal activity.

9. A method of predicting or detecting the occurrence of abnormal activity in the brain of a subject, said method comprising the steps of:

(a) receiving into a signal processor input signals indicative of a subject'"'"'s brain activity;

(b) analyzing said signals to detect at least one precursor predictive of the occurrence of abnormal activity in the subject; and

(c) upon occurrence of said at least one precursor, producing an output in response thereto before the onset of electroencephalographic waves signaling the occurrence of the abnormal activity;

step (b) including the step of detecting said at least one precursor by applying a signal analysis filter to detect individual spikes in said input signals and then determining whether said detected individual spikes are predictive of said abnormal activity.

10. The method of claim 9, wherein said abnormal activity is identified by measuring interarrival times of said detected spikes.

11. A method of predicting or detecting the occurrence of abnormal activity in the brain of a subject, said method comprising the steps of:

(a) receiving into a signal processor input signals indicative of a subject'"'"'s brain activity;

(b) analyzing said signals to detect at least one precursor predictive of the occurrence of abnormal activity in the subject; and

(c) upon occurrence of said at least one precursor, producing an output in response thereto before the onset of electroencephalographic waves signaling the occurrence of the abnormal activity;

(d) wherein step (b) includes the step of detecting said precursor by determining a ratio of foreground median frequency to background median frequency and determining whether said ratio reaches a predetermined level, such being predictive of the abnormal activity.

12. A method of detecting or predicting the occurrence of abnormal activity in the brain of a subject, said method comprising the steps of:

(a) receiving into a signal processor input signals indicative of a subject'"'"'s brain activity;

(b) measuring at least one attribute of said input signals in a foreground epoch thereof wherein said at least one attribute is selected from a group of attributes of said input signals comprising complexity, phase relationships, coherence, dimension, rhythmicity, and sequency of said input signals;

(c) determining whether said foreground measure is indicative of the occurrence of said abnormal activity; and

(d) performing steps (a)-(c) while said ictal activity is occurring before the onset of electroencephalographic waves of said abnormal activity.

13. A method of detecting or predicting the occurrence of abnormal activity in the brain of a subject, said method comprising the steps of:

(a) receiving into a signal processor input signals indicative of a subject'"'"'s brain activity;

(b) analyzing said input signals to detect at least one precursor predictive of the occurrence of a seizure in the subject; and

(c) upon occurrence of said at least one precursor, producing an output in response thereto before the onset of electroencephalographic waves signaling the occurrence of the seizure;

wherein step (b) includes the step of detecting, and classifying or counting at least one spike of said input signals.

14. A method of predicting or detecting the occurrence of abnormal activity in the brain of a subject, said method comprising the steps of:

(a) receiving into a signal processor input signals indicative of a subject'"'"'s brain activity;

(b) analyzing said signals to detect at least one precursor predictive of the occurrence of a seizure in the subject; and

(c) upon occurrence of said at least one precursor, producing an output in response thereto before the onset of electroencephalographic waves signaling the occurrence of the seizure;

wherein step (b) includes the step of utilizing single wave analysis.

15. The method of claim 14, wherein said single wave analysis utilizes cluster analysis.

16. A method of detecting or predicting the occurrence of abnormal activity in the brain of a subject, said method comprising the steps of:

(a) receiving into a signal processor input signals taken from biological signals representative of biological functions selected from the group consisting of respiratory activity and gases, concentrations of glucose, free radicals, indices of metabolic activity including metabolic by-products, electrolytes, neurotransmitters and other substances in blood, brain and/or other body tissues, brain temperature, intracranial pressure, blood flow, heart activity, muscle activity, ocular activity, magnetic fields, skin resistance and temperature, and electrical fields indicative of a subject'"'"'s brain activity;

(b) analyzing said signals to detect at least one precursor predictive of the occurrence of abnormal activity in the subject; and

(c) upon occurrence of said at least one precursor, producing an output in response thereto before the onset of electroencephalographic waves signaling the occurrence of the abnormal activity.

17. A method of predicting or detecting the occurrence of abnormal activity in the brain of a subject, said method comprising the steps of:

(a) receiving into a signal processor input signals indicative of a subject'"'"'s brain activity;

(b) analyzing said signals utilizing alpha-trimmed means or weighted averages to detect at least one precursor predictive of the occurrence of abnormal activity in the subject; and

(c) upon occurrence of said at least one precursor, producing an output in response thereto before the onset of electroencephalographic waves signaling the occurrence of the abnormal activity.

18. An apparatus for predicting or detecting the occurrence of abnormal activity in the brain of a subject, comprising:

(a) a signal processor configured to receive input signals indicative of a subject'"'"'s brain activity;

(b) a first determining mechanism, including a first filter mechanism, configured to extract and enhance ictal components of the input signals received by said signal processor;

(c) a second filter mechanism configured to measure ictal activity in said ictal components extracted and enhanced by said first filter mechanism in a foreground epoch of said input signals by applying a foreground order-statistic filter to said ictal components corresponding to said foreground epoch to produce a foreground measure of said ictal activity corresponding thereto; and

(d) a second determining mechanism configured to determine whether said foreground measure reaches a threshold level indicative of the occurrence of abnormal activity in the subject'"'"'s brain before the onset of electroencephalographic waves of said abnormal activity.

19. The apparatus as set forth in claim 18, wherein said first filter mechanism includes a digital filter.

20. The apparatus as set forth in claim 19, wherein said digital filter includes a finite impulse response filter.

21. The apparatus as set forth in claim 19, wherein said digital filter includes an infinite impulse response filter.

22. The apparatus as set forth in claim 19, wherein said digital filter includes at least one single wave analysis filter.

23. The apparatus as set forth in claim 18, wherein said first filter mechanism includes an analog filter.

24. The apparatus as set forth in claim 18, wherein said first determining mechanism includes a squaring mechanism configured to square the results provided by said first filter mechanism to determine said ictal components.

25. The apparatus as set forth in claim 18, further including:

(a) a third filter mechanism configured to measure background ictal activity in said ictal components extracted and enhanced by said first and second filter mechanisms in a background epoch of said input signals by applying a background order-statistic filter to said ictal components corresponding to said background epoch to produce a background measure of said ictal activity corresponding thereto, said background epoch occurring before said foreground epoch with a time delay between said foreground and background epochs; and

(b) said second determining mechanism is further configured to determine whether a ratio of said foreground measure to said background measure reaches a predetermined level indicative of the occurrence of said abnormal activity.

26. The apparatus as set forth in claim 18, wherein said foreground order-statistic filter and said background order-statistic filter are further configured to present a time delay between said foreground and background epochs.

27. The apparatus as set forth in claim 26, wherein said foreground order-statistic filter and said background order-statistic filter are further configured to use a time interval of approximately two seconds for said foreground epoch, a time interval of approximately twenty seconds for said back ground epoch, and a time interval of approximately one second for said time delay.

28. The apparatus as set forth in claim 25, wherein said foreground and background order-statistic filters are further configured to continuously update said foreground and background measures.

29. The apparatus as set forth in claim 28, wherein said background order-statistic filter is further configured to suspend updating of said background measure if said ratio reaches a second threshold level.

30. The apparatus as set forth in claim 25, wherein:

(a) said first determining mechanism is further configured such that said first filter mechanism includes one of a finite impulse response filter and an infinite impulse response filter configured to enhance said ictal components by squaring output results obtained from application of said first filter mechanism;

(b) said first and second determining mechanisms are further configured to respectively update said foreground and background measures; and

(c) said background order-statistic filter is further configured to suspend updating of said background measure if said ratio reaches a third threshold level.

31. The apparatus as set forth in claim 18, wherein said first determining mechanism is further configured to select said first filter mechanism from a filter bank having a plurality of filter mechanisms configured to extract and enhance said ictal components.

32. The apparatus as set forth in claim 21, wherein said first determining mechanism is further configured to select said first filter mechanism as the filter mechanism from said filter bank providing the greatest differentiation of ictal components from non-ictal components of said input signals.

33. The apparatus as set forth in claim 18, wherein said first filter mechanism is further configured to increase the differentiation of ictal components of the subject from non-ictal components.

34. The apparatus as set forth in claim 18, wherein said signal processor is further configured to receive said input signals from at least one electrode operable for detecting a subject'"'"'s brain activity, wherein said at least one electrode is selected from the group consisting of a scalp electrode and an implanted electrode.

35. The apparatus as set forth in claim 18, wherein said signal processor is further configured to receive said input signals from a memory-device.

36. The apparatus as set forth in claim 18, wherein said signal processor is selected from the group consisting of a microprocessor and a computer.

37. The apparatus as set forth in claim 18, wherein said first filter mechanism includes a wavelet filter configured to determine corresponding wavelet coefficients of said input signals, to use said wavelet coefficients to determine a power density distribution, and to compare said power density distribution with said threshold level wherein a crossing of said threshold level by said power density distribution indicates the occurrence of said abnormal activity.

38. The apparatus as set forth in claim 18, wherein said first filter mechanism is configured to analyze said input signals using windowed Fourier and inverse Fourier transforms.

39. The apparatus as set forth in claim 18, further including an output mechanism configured to produce an output in response to an indication of an occurrence of a seizure as said abnormal activity, wherein said output mechanism is taken from the group consisting of administering a medicament or other selected substance, electrically stimulating a portion of the subject'"'"'s brain, delivering electromagnetic energy to a selected portion of the subject, magnetically stimulating a portion of the subject'"'"'s brain, inhibiting activity in a portion of the subject'"'"'s brain, electrically stimulating a nerve of the subject, recording said signals, transmitting said signals, activating a warning mechanism, activating a biofeedback mechanism, stimulating physiological receptors of the subject, heating at least a portion of the subject'"'"'s brain, cooling at least a portion of the subject'"'"'s brain, facilitating activity in a portion of the subject'"'"'s brain, disfacilitating activity in a portion of the subject'"'"'s brain, and ablating a portion of the subject'"'"'s brain.

40. The apparatus as set forth in claim 18, wherein at least a portion of said apparatus is configured to be implanted within the subject.

41. The apparatus as set forth in claim 18, wherein said first filter mechanism is selected from a group consisting of filters designed to use random search algorithms, evolving algorithms, and genetic algorithms.

42. The apparatus as set forth in claim 41, wherein said first filter mechanism is further configured to select an optimized filter from said group.

43. The apparatus as set forth in claim 18, wherein said first filter is taken from the group consisting of a digital filter, a nonlinear filter, an adaptive filter, a correlation integral filter, an arc length differential filter, and a temperature filter.

44. The apparatus as set forth in claim 18, wherein said apparatus is configured to predict and detect the occurrence of an epileptic seizure as said abnormal activity.

45. The apparatus as set forth in claim 18, wherein said signal processor is further configured to receive other biological signals of the subject and to use said biological signals to detect the occurrence of a seizure as said abnormal activity, said biological signals being representative of biological functions of the subject selected from the group consisting of respiratory activity and gases, concentrations of glucose, free radicals, indices of metabolic activity including metabolic by-products, electrolytes, neurotransmitters and other substances in blood, brain and/or other body tissues, brain temperature, intracranial pressure, blood flow, heart activity, muscle activity, ocular activity, magnetic fields, skin resistance and temperature, and electrical fields.

46. The apparatus as set forth in claim 18, wherein at least a portion of said apparatus is further configured to be portable.

47. The apparatus as set forth in claim 18, wherein at least a portion of said apparatus is further configured to be implantable within the subject.

48. An apparatus for predicting or detecting the occurrence of abnormal activity in the brain of a subject, comprising:

(a) a signal processor configured to receive input signals indicative of a subject'"'"'s brain activity;

(b) a first determining mechanism, including a first determining filter mechanism configured to extract ictal components in a foreground epoch of said input signals received by said signal processor, configured to produce a foreground measure of ictal activity in said foreground epoch;

(c) a second determining mechanism, including a second determining filter mechanism configured to extract ictal components in a background epoch of said input signals received by said signal processor, configured to produce a background measure of ictal activity in said background epoch; and

(d) a third determining mechanism configured to determine whether a ratio of said foreground measure to said background measure reaches a threshold level indicative of the occurrence of abnormal activity in the subject'"'"'s brain before the onset of electroencephalographic waves of said abnormal activity, wherein said ratio is determined by comparing said foreground measure against a background signal generated using time- and state-weighted averaging of said background ictal components.

49. The apparatus as set forth in claim 48, wherein said second determining mechanism is further configured to use an exponentially forgetting time averaging as said time- and state-weighted averaging of said extracted background ictal components.

50. An apparatus for predicting or detecting the occurrence of a seizure in the brain of a subject, comprising:

(a) a signal processor configured to receive input signals indicative of a subject'"'"'s brain activity;

(b) an analyzing mechanism configured to analyze said input signals to detect at least one precursor predictive or indicative of the occurrence of a seizure in the subject; and

(c) an output mechanism configured to produce an output in response thereto before the onset of electroencephalographic waves signaling the occurrence of the seizure upon the occurrence of said at least one precursor.

51. The apparatus as set forth in claim 50, wherein said analyzing mechanism is further configured to detect said at least one precursor by determining a ratio of background signal energy in at least one frequency band compared to current signal energy in said at is least one band and determining whether said ratio reaches a predetermined level, such being predictive of the seizure.

52. The apparatus as set forth in claim 50, wherein said analyzing mechanism is further configured to quantify at least one seizure characteristic, wherein said at least one seizure characteristic is selected from the group consisting of seizure onset location, seizure pattern of spread, seizure duration, seizure intensity, seizure time-frequency evolution, and frequency of seizure occurrence.

53. The apparatus as set forth in claim 50, wherein said analyzing mechanism is further configured to provide post-ictal validation of a seizure prediction or detection of a post-ictal state by measuring whether said seizure is followed by a drop in signal energy in at least one frequency band, said drop reaching a level indicative of a post-ictal state.

54. The apparatus as set forth in claim 53, wherein said analyzing mechanism is further configured to determine a duration of a post-ictal state by measuring the time interval that said signal energy in said at least one band remains in a range indicative of a post-ictal state.

55. The apparatus as set forth in claim 50, wherein said analyzing mechanism is further configured to utilize alpha-trimmed means or weighted averages to detect said at least one precursor.

56. The apparatus as set forth in claim 50, wherein said analyzing mechanism is further configured to detect spikes in said input signals wherein each such spike presents a polarity, to determine the sharpness of each said spike by determining a parabola of optimal fit thereof, to determine an index of relative sharpness of each said spike by comparing the sharpness thereof to sharpnesses of other spikes in a time window of said input signals, to determine whether said index reaches a predetermined level, and to determine whether said indices reaching said predetermined level are predictive of a seizure.

57. The apparatus as set forth in claim 50, wherein said analyzing mechanism includes a signal analysis filter and is configured to detect individual spikes in said input signals, and to determine whether said detected individual spikes are predictive of said abnormal activity.

58. The apparatus of claim 57, wherein said analysis mechanism is further configured to measure interarrival times of said spikes.

59. The apparatus as set forth in claim 50, wherein said analyzing mechanism is configured to detect said precursor by determining a ratio of foreground median frequency to background median frequency and determining whether said ratio reaches a predetermined level, such being predictive of a seizure.

60. The apparatus as set forth in claim 50, wherein said analyzing mechanism is further configured to detect epileptiform waves in said input signals having a characteristic shape, amplitude, pattern or temporal spatial probability distribution that is predictive of a seizure.

61. An apparatus for analyzing the activity state of the brain of a subject, comprising:

(a) a signal processor configured to receive input signals representative of a subject'"'"'s brain activity and to analyze said signals for the presence therein of information indicating the current activity state of the subject'"'"'s brain while said activity state is occurring; and

(b) an output mechanism configured to produce an output in response to said presence of said information prior to the onset of electroencephalographic waves of said signals indicating an impending change in activity state of the brain of the subject.

62. The apparatus as set forth in claim 61, wherein said signal processor is configured to analyze said signals by detecting and classifying or counting at least one spike in said signals.

63. The apparatus as set forth in claim 61, wherein said signal processor is configured to analyze said signals by quantifying at least one seizure characteristic therein, wherein said at least one seizure characteristic is selected from the group consisting of seizure onset location, seizure pattern of spread, seizure duration, seizure intensity, seizure time-frequency evolution, and frequency of seizure occurrence.

64. The apparatus as set forth in claim 61, wherein said signal processor is configured to analyze said signals by performing a single wave analysis on said signals.

65. The apparatus as set forth in claim 64, wherein said signal processor is further configured to utilize cluster analysis to analyze said signals.

66. The apparatus as set forth in claim 64, wherein said signal processor is further configured to measure at least one attribute of said input signals in a foreground epoch thereof, wherein said at least one attribute is selected from a group of attributes of said input signals comprising complexity, phase relationships, coherence, dimension, rhythmicity and sequency of said input signals, to determine the presence of said information.

67. An apparatus for predicting or detecting the occurrence of abnormal activity in the brain of a subject, comprising:

(a) a signal processor configured to receive input signals indicative of a subject'"'"'s brain activity;

(b) a first determining mechanism configured to determine the presence of at least one ictal component in said input signals;

said first determining mechanism including a measuring mechanism configured to measure the ictal activity indicated by said at least one ictal component in said input signals and to produce a measure of said ictal activity; and

(c) a second determining mechanism configured to determine whether said measure of said ictal activity is indicative of the occurrence of an abnormal activity in the subject'"'"'s brain while said ictal activity is occurring but before the onset of electroencephalographic wave signals of said abnormal activity.

68. The apparatus as set forth in claim 67, wherein said apparatus is configured to detect the occurrence of abnormal activity wherein said abnormal activity is selected from the group including a seizure and at least one spike.

69. The apparatus as set forth in claim 67, wherein said measuring mechanism includes an order-statistic filter configured to produce said measure of ictal activity from said at least one ictal component.

70. The apparatus as set forth in claim 67, wherein said second determining mechanism is further configured to determine whether said ictal activity reaches a threshold level indicative of the occurrence of said abnormal activity.

71. The apparatus as set forth in claim 67, wherein said second determining mechanism is further configured to determine whether said ictal activity reaches an adaptive threshold level indicative of the occurrence of said abnormal activity.

72. The apparatus as set forth in claim 67, wherein said second determining mechanism is further configured to determine whether said ictal activity of said measure is indicative of the occurrence of said abnormal activity while said ictal activity is occurring but before the onset of a clinical component indicative of the occurrence of said abnormal activity.

73. The apparatus as set forth in claim 67, wherein said measuring mechanism is further configured to determine whether said ictal activity of said foreground measure is indicative of the occurrence of said abnormal activity while said ictal activity is occurring but before the onset of a selected at least one biological signal indicative of the occurrence of said abnormal activity, said at least one biological signal being representative of a respective biological function of the subject selected from the group consisting of respiratory activity and gases, concentrations of glucose, free radicals, indices of metabolic activity including metabolic by-products, electrolytes, neurotransritters and other substances in blood, brain and/or other body tissues, brain temperature, intracranial pressure, blood flow, heart activity, muscle activity, ocular activity, magnetic fields, skin resistance and temperature, and electrical fields.

74. The apparatus as set forth in claim 67, further including an output mechanism configured, responsive to said second determining mechanism, to provide information to the subject regarding said at least one ictal component of the input signals for the purpose of initiating biofeedback to the subject indicative of a selected activity state of the brain of the subject.

75. An apparatus for predicting or detecting the occurrence of abnormal activity in the brain of a subject, comprising:

(a) a signal processor configured to receive input signals indicative of a subject'"'"'s brain activity;

(b) a first determining mechanism configured to determine at least one ictal component and at least one non-ictal component in said input signals;

(c) a measuring mechanism configured to measure the ictal activity indicated by said at least one ictal component in a foreground epoch of said input signals to produce a foreground measure of said ictal activity; and

(d) a second determining mechanism configured to determine whether said ictal activity of said foreground measure is indicative of the occurrence of said abnormal activity while said abnormal activity is occurring but before the onset of electrocorticogram wave signals of said abnormal activity.

76. The apparatus as set forth in claim 75, wherein said second determining mechanism is further configured to determine whether said activity of said foreground measure is indicative of the occurrence of said abnormal activity while said abnormal activity is occurring but before the onset of a selected clinical component indicative of the occurrence of said abnormal activity.