Cerebral biopotential analysis system and method

• US 5,458,117 A
• Filed: 06/09/1994
• Issued: 10/17/1995
• 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: Sigl, Jeffrey C., Chamoun, Nassib G., Smith, Charles P.
• Primary Examiner(s): MANUEL, GEORGE C
• Application Number:
  US08/257,356
• Time in Patent Office: 495 Days
• Field of Search: 128/731, 128/732, 128/734, 128/733, 128/635, 364/413.01, 364/413.02, 364/413.03, 364/413.04, 364/413.05, 364/413.06
• US Class Current: 600/547
• 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 system and method to derive a diagnostic index indicative of a selected cerebral phenomena which obtains 19 unipolar EEG signals from regions of interest on both the left and right hemispheres of a subject'"'"'s brain. The system uses high-gain, low-noise amplifiers to maximize the dynamic range for low energy wave components of the signals. Band-pass filtering is used to reduce noise and to avoid aliasing. The system applies commonly used digital signal processing (DSP) techniques to digitize, to low-pass filter (100 Hz), and to decimate the signals. Power spectral, bispectral, and higher-order spectral processing is then performed. In a preferred embodiment, the system divides the most recent 63 seconds of digitized EEG data from each lead into 60 4-second intervals, each with 3 seconds of overlap with the previous interval. For a selected set of derived leads, the system produces auto power spectrum, autobispectrum, and auto higher-order spectrum variables, by using either a Fast Fourier Transform (FFT) based approach or a parametric approach. Any pair of leads can be combined to compute cross power spectrum, cross bispectrum, and cross higher-order spectrum variables. The spectral values are separated into bins and a value representative of the bin is selected or computed and then each value is multiplied by a predetermined coefficient. The resulting products are summed to arrive at the diagnostic index.

Claims

1. A method of generating a diagnostic index for quantifying the presence or absence of a biopotential phenomena, said method comprising the steps of:

acquiring electrical signals from a living body, said electrical signals representing the biopotential phenomena;

generating spectral values from said acquired electrical signals;

sorting said spectral values into at least one predetermined bin of ranges of spectral values;

selecting at least one variable representative of spectral values in each of said at least one bin;

multiplying said selected at least one variable in each of said at least one 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.

2. The method of generating a diagnostic index of claim 1 wherein said spectral values are power spectrum values.

3. The method for generating a diagnostic index of claim 1 wherein said spectral values are bispectrum values.

4. The method of generating a diagnostic index of claim 1 wherein said spectral values are kth order spectral values where k is greater than 2.

5. The method of generating a diagnostic index of claim 1 wherein said at least one variable ms the mean of the spectral values in said bin.

6. The method of generating a diagnostic index of claim 1 wherein said at least one variable ms the median of the spectral values in said bin.

7. The method of generating a diagnostic index of claim 1 wherein said at least one variable ms the standard deviation of the spectral values in said bin.

9. The method of generating a diagnostic index of claim 1 wherein said at least one variable ms the minimum value of the spectral values in said bin.

10. The method of generating a diagnostic index of claim 1 wherein said at least one variable ms a preselected positional value from said bin.

11. The method of generating a diagnostic index of claim 1 wherein said at least one variable is a specified rank ordered variable.

8. The method of generating a diagnostic index of claim t wherein said at least one variable ms the maximum value of the spectral values in said bin.

12. A system for generating a diagnostic index for quantifying the presence or absence of a biopotential phenomena, said system comprising:

means for acquiring electrical signals from a living body, said electrical signals representing the biopotential phenomena;

means for generating spectral values from said acquired electrical signals;

means for sorting said spectral values into at least one predetermined bin of ranges of spectral values;

means for selecting at least one variable representative of the spectral values in each of said at least one bin;

means for multiplying said selected at least one variable in each of said at least one 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.

13. The system for generating a diagnostic index of claim 12 wherein said spectral values are power spectrum values.

14. The system for generating a diagnostic index of claim 12 wherein said spectral values are bispectrum values.

15. The system for generating a diagnostic index of claim 12 wherein said spectral values are kth order spectral values where k is greater than 2.

16. The system for generating a diagnostic index of claim 12 wherein said at least one variable is the mean of the spectral values in said bin.

17. The system for generating a diagnostic index of claim 12 wherein said at least one variable is the median of the spectral values in said bin.

18. The system for generating a diagnostic index of claim 12 wherein said at least one variable is the standard deviation of the spectral values in said bin.

19. The system for generating a diagnostic index of claim 12 wherein said at least one variable is the maximum value of the spectral values in said bin.

20. The system for generating a diagnostic index of claim 12 wherein said at least one variable is the minimum value of the spectral values in said bin.

21. The system for generating a diagnostic index of claim 12 wherein said at least one variable is a preselected positional value from said bin.

22. The system for generating a diagnostic index of claim 12 wherein said at least one variable is a specified rank ordered variable.