Apparatus and methods for brain rhythm analysis

• US 7,299,088 B1
• Filed: 06/01/2003
• Issued: 11/20/2007
• Est. Priority Date: 06/02/2002
• Status: Expired due to Fees

• Current Assignee: Anastasios Bezerianos, David Sherman, Feras Al Hatib, Hasan Al-Nashash, Joseph Paul, Nitish V. Thakor, Santosh Venkatesha, Shanbao Tong
• Original Assignee: Anastasios Bezerianos, David Sherman, Feras Al Hatib, Hasan Al-Nashash, Joseph Paul, Nitish V. Thakor, Santosh Venkatesha, Shanbao Tong
• Inventors: Venkatesha, Santosh, Thakor, Nitish V, Paul, Joseph, Sherman, David, Al Hatib, Feras, Tong, Shanbao, Al-Nashash, Hasan, Bezerianos, Anastasios
• Primary Examiner(s): Nasser; Robert L.
• Application Number:
  US10/452,190
• Time in Patent Office: 1,633 Days
• Field of Search: 600/382, 600/383, 600/384
• 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 5/4812 Detecting sleep stages or cycles
• CPC Class Codes: A61B 5/4821 Determining level or depth of anaesthesia A61B5/1106 takes precedence
• CPC Class Codes: A61B 5/726 using Wavelet transforms
• CPC Class Codes: G06F 2218/08 Feature extraction

Abstract

Embodiments include methods and apparatus for determining whether a neurological event has occurred in a subject. An apparatus includes at least one sensor adapted to sense electroencephalogram signals from the subject. The apparatus also includes an electroencephalogram acquisition module adapted to receive the electroencephalogram signals from at least one sensor, and a processing and analysis module adapted to receive signals from the electroencephalogram acquisition module and determine changes in neurological function using entropy analysis.

Claims

1. A method of monitoring neurological function, comprising:

acquiring electroencephalogram signals from a subject; and

processing and analyzing data from the electroencephalogram signals using at least one entropy method selected from the group consisting of;

Shannon entropy, Tsallis entropy, Renyi entropy, time dependent entropy, time multi-resolution dependent entropy, relative time dependent entropy, relative time multi-resolution dependent entropy, residual time dependent entropy, residual time multi-resolution dependent entropy, subband wavelet entropy, multi-resolution wavelet entropy, relative subband wavelet entropy, relative multi-resolution wavelet entropy, residual subband wavelet entropy, and residual multi-resolution wavelet entropy;

wherein the processing and analyzing data includes analyzing at least one electroencephalogram waveform segment, wherein the at least one electroencephalogram waveform segment comprises a plurality of data points from the electroencephalogram signal; and

wherein the processing and analyzing data further comprises calculating the maximum and minimum amplitude value of the data points from the at least one electroencephalogram waveform segment and determining an amplitude domain with upper and lower amplitude boundaries based on statistical analysis and processing of the maximum and minimum amplitude values of the at least one electroencephalogram waveform segment.

2. A method as in claim 1, wherein the processing and analyzing data further comprises determining sub-intervals partitioned from the amplitude domain, calculating the occurrence of data points from the at least one electroencephalogram waveform segment in the sub-intervals, and tabulating the calculated information into a statistical array.

3. A method as in claim 1, wherein the statistical array comprises a histogram.

4. A method as in claim 2, wherein the processing and analyzing data further comprises deriving a probability calculation with statistical methods for determining the occurrence of data points from the at least one electroencephalogram waveform segment in the sub-intervals.

5. A method as in claim 2, wherein the processing and analyzing data further comprises calculating entropy values with the at least one entropy method using the probability calculation for the occurrence of data points from the at least one electroencephalogram waveform segment in the sub-intervals.

6. A method as in claim 5, further comprising storing and displaying the entropy values.