Method for amplifying abnormal pattern signal in observed brain activity of a subject for diagnosis or treatment

• US 8,538,512 B1
• Filed: 10/28/2008
• Issued: 09/17/2013
• Est. Priority Date: 04/23/2007
• Status: Active Grant

• Current Assignee: NeuroWave Systems Inc.
• Original Assignee: NeuroWave Systems Inc.
• Inventors: Bibian, Stphane, Zikov, Tatjana, Modarres, Mohammad
• Primary Examiner(s): Kahelin, Michael
• Assistant Examiner(s): TRAN, THO Q
• Application Number:
  US12/259,652
• Time in Patent Office: 1,785 Days
• Field of Search: 600/544
• US Class Current: 600/544
• CPC Class Codes: A61B 5/0006 ECG or EEG signals
• CPC Class Codes: A61B 5/1128 using image analysis A61B5/1127 takes precedence
• CPC Class Codes: A61B 5/24 Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• 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 5/4839 combined with drug delivery
• CPC Class Codes: A61B 5/721 using a separate sensor to detect motion or using motion information derived from signals other than the physiological signal to be measured
• CPC Class Codes: A61B 5/7235 Details of waveform analysis A61B5/349 takes precedence
• CPC Class Codes: A61B 5/743 Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
• CPC Class Codes: A61N 1/36064 Epilepsy

Abstract

The present invention relates to a brain dysfunction and seizure detector monitor and system, and a method of detecting brain dysfunction and/or seizure of a subject. The various embodiments of the system of the present invention were developed for the brain activity and preferably EEG monitoring of a single patient or multiple patients. Preferably, the system or monitor of the present invention also includes one or more seizure detection algorithms. The analysis method is specifically optimized to amplify abnormal brain activity and minimize normal background activity. This analysis yields a seizure index whose value is directly related to the current presence of ictal activity in the signal. In addition, a seizure probability index based on historical values of the aforementioned seizure index, is derived for diagnostic purposes. The seizure probability index quantifies the probability that the patient has exhibited abnormal brain activity since the beginning of the recording. The real-time seizure index, and the historical seizure probability index, can be used in the context of an emergency and/or clinical situation to assess the status and well being of a patient'"'"'s brain, or can be used to automatically administer treatment to stop the seizure before clinical signs appear.

Claims

1. A method for amplifying abnormal pattern signals in observed brain activity of a subject for diagnosis or treatment purposes comprising the steps of

acquiring at least one electrophysiological signal with a sensor from the subject,

applying a transform to the at least one electrophysiological signal with a processor to obtain coefficients from the electrophysiological signal in a number of frequency bands,

aligning the coefficients to synchronize an abnormal pattern signal in the different frequency bands,

combining the aligned coefficients to amplify the abnormal pattern signals indicative of abnormal brain activity, and

using the amplified abnormal pattern signal to diagnose or treat the subject.

2. The method of claim 1, where the abnormal brain activity is seizure activity.

3. The method of claim 1, where the transform is a joint time-frequency transform.

4. The method of claim 1, where the aligning the coefficients is done by shifting in time the coefficients by a number of sample times greater or equal to 0.

5. The method of claim 1, where the combining the aligned coefficients is done through a non-linear function of said aligned coefficients.

6. The method of claim 1, where the amplified abnormal pattern signal is used to quantify the effect of a medical treatment.

7. A method for amplifying abnormal pattern signals in observed brain activity of a subject for diagnosis or treatment purposes comprising the steps of

acquiring at least one electrophysiological signal with a sensor from the subject,

applying a redundant time-frequency transform to the at least one electrophysiological signal with a processor to obtain coefficients in a number of frequency bands,

combining the coefficients to amplify abnormal pattern signals in at least one of the different frequency bands indicative of abnormal brain activity, and

using the amplified abnormal pattern signals to diagnose or treat the subject.

8. The method of claim 7, where the abnormal brain activity is seizure activity.

9. The method of claim 7, where the redundant time-frequency transform is a redundant wavelet packet transform.

10. The method of claim 7, where the amplified abnormal pattern signal is used to diagnose abnormal brain activity in the subject at the scene of an accident.

11. The method of claim 7, where the amplified abnormal pattern signal is used to quantify the effect of a medical treatment.

12. A method for amplifying abnormal pattern signals in observed brain activity of a subject for diagnosis or treatment purposes comprising the steps of

acquiring at least one electrophysiological signal with a sensor from the subject,

applying a redundant time-frequency transform to the at least one electrophysiological signal with a processor to obtain coefficients in a number of frequency bands,

combining said coefficients to amplify abnormal pattern signals in at least one of the different frequency bands indicative of abnormal brain activity,

applying a filter or an integrator to the amplified abnormal pattern signal to reduce noise, and

using the filtered or integrated amplified abnormal pattern signal to diagnose or treat the subject.

13. The method of claim 12, where the abnormal brain activity is seizure activity.

14. The method of claim 12, where the transform is a redundant wavelet packet transform.

15. The method of claim 12, further comprising a step of aligning the coefficients to synchronize an abnormal pattern signal in the different frequency bands, and where the aligning the coefficients is done by shifting in time the coefficients by a number of sample times greater or equal to 0.

16. The method of claim 12, where the integrating of the amplified abnormal pattern signal is done through a resettable integrator.

17. The method of claim 12, where the filtering of the amplified abnormal pattern signal is done by setting the amplified abnormal pattern signal to 0 whenever the amplified abnormal pattern signal is less than a defined threshold for a defined duration in time, and integrating the amplified abnormal pattern signal whenever the amplified abnormal pattern signal is more than a threshold.

18. The method of claim 12, where the filtering of the amplified abnormal pattern signal is done by setting the amplified abnormal pattern signal to 0 whenever the amplified abnormal pattern signal is less than a defined threshold for a defined duration in time, and integrating said amplified abnormal pattern signal whenever the amplified abnormal pattern signal is more than a threshold and resetting the integrator when the amplified abnormal pattern signal has been less than a defined threshold for at least a duration of one 1 sample or more.

19. The method of claim 12, where the amplified and filtered abnormal pattern signal is used to quantify the effect of a medical treatment.

20. A method for detecting abnormal brain activity or seizure activity of a subject for diagnosis or treatment purposes comprising the steps of

acquiring at least one electrophysiological signal with a sensor from the subject,

applying a redundant time-frequency transform to the at least one electrophysiological signal with a processor to obtain coefficients in a number of frequency bands,

combining the coefficients to amplify abnormal pattern signals in at least one of the different frequency bands indicative of abnormal brain activity or seizure activity,

filtering or integrating the amplified pattern signal to reduce noise, and

comparing the filtered or integrated amplified pattern signal to a threshold to trigger an alarm indicative of an abnormal brain activity or seizure being detected that alerts a clinician or other user.

21. The method of claim 20, where the threshold can be changed manually by a user.

22. The method of claim 20, where the alarm threshold can be adapted automatically based on the patient'"'"'s present brain state at the time.

23. The method of claim 20, where the amplified and filtered abnormal pattern signal is used to quantify the effect of a medical treatment.