Method and system for limiting interference in electroencephalographic signals

• US 20070038382A1
• Filed: 08/09/2005
• Published: 02/15/2007
• Est. Priority Date: 08/09/2005
• Status: Active Grant

• Current Assignee: Adidas AG
• Original Assignee: Adidas AG
• Inventors: Keenan, Barry
• Granted Patent: US 7,809,433 B2
• Time in Patent Office: Days
• US Class Current: 702/19
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A61B 5/726 using Wavelet transforms
• CPC Class Codes: G06F 2218/04 Denoising

Abstract

This invention provides methods and systems for removing or limiting interference and artifacts often found in EEG signals and/or EOG signals and/or other physiological signals, and produces output signals that can be of greater use for analytic or diagnostic purposes, such as sleep studies. Interference and artifacts are removed by applying a plurality of filtering methods targeted to the particular time-frequency characteristics of the anticipated interference.

Claims

1. A method for processing a physiological signal of interest also comprising unwanted spurious signals, the method comprising:

limiting at least one narrow-band spurious signal by

performing one or more windowed Fourier transforms on one or more segments of said physiological signal, and

filtering Fourier coefficients having temporal variation substantially less than the temporal variation of said physiological signal and having relative temporal duration substantially greater than relative frequency bandwidth, a relative temporal duration being a temporal duration in comparison to the temporal duration of the signal segment being processed, and a relative frequency bandwidth being a bandwidth in comparison to the bandwidth of the signal segment being processed; and

limiting at least one intermittently-occurring spurious signal by

performing one or more wavelet transforms on one or more segments of said physiological signal, and

filtering wavelet coefficients having characteristics that are distinguishable from said physiological signal of interest and having relative temporal duration substantially less than relative frequency bandwidth.

2. The method of claim 1 wherein Fourier coefficients are found to have a temporal variation substantially less than the temporal variation of said physiological signal if the standard deviation of said coefficients is less than a threshold

3. The method of claim 2 wherein said threshold depends on a standard deviation of said Fourier coefficients of interest.

4. The method of claim 1 wherein said filtering Fourier coefficients further comprises

determining the zero-crossing bandwidth of Fourier coefficients;

and

limiting the amplitudes of Fourier coefficients within said zero-crossing bandwidth.

5. The method of claim 1 wherein wavelet coefficients are distinguishable if said coefficients have amplitudes greater than a threshold.

6. The method of claim 5 wherein said threshold varies in dependence on the amplitude of wavelet coefficients of said physiological signal of interest and on the amplitude of wavelet coefficients of said intermittently occurring spurious signal.

7. The method of claim 6 wherein said threshold varies in dependence on the means and standard deviations of said wavelet coefficient.

8. The method of claim 1 wherein said filtering wavelet coefficients further comprises applying a threshold function to said wavelet coefficients.

9. The method of claims 8 wherein said threshold function sets to zero wavelet coefficients having amplitudes exceeding a threshold value.

10. The method of claim 1 further comprising

performing at least one inverse Fourier transform of said filtered Fourier coefficients;

performing at least one inverse wavelet transform of said filtered wavelet coefficients; and

outputting the signal resulting from said inverse Fourier transform and said inverse wavelet transform.

11. The method of claim 1 wherein said narrow-band spurious signals comprise signals having a relative temporal duration greater than or equal to approximately five times the relative frequency bandwidth of said signals.

12. The method of claim 1 wherein said intermittently-occurring spurious signals comprise signals having a relative temporal duration less than or equal to approximately two times the relative frequency bandwidth of said signals.

13. The method of claim 1 wherein the total temporal duration of all occurrences of said intermittently-occurring spurious signals is less than or equal to approximately one-fifth of the total temporal duration of the signal segment being processed.

14. The method of claim 1 wherein said intermittently-occurring spurious signals comprise at least one occurrence of a QRS wave.

15. The method of claim 14

wherein said filtering wavelet coefficients further comprises applying a threshold function to said wavelet coefficients;

and

wherein said threshold value is between a first expected amplitude of wavelet coefficients not in a vicinity of any QRS wave occurrence and a second expected amplitude of distinguishable wavelet coefficients in the vicinity of at least one QRS wave occurrence.

16. The method of claim 15 wherein vicinities of QRS wave occurrences are determined by a QRS detection method applied to a physiological signal.

17. The method of claim 15 wherein said first and/or second expected amplitudes are determined in dependence on the means and standard deviations of wavelet coefficients.

18. The method of claim 1 wherein said physiological signals comprise one or more of electroencephalographic (EEG) signals, and/or electrooculographic (EOG) signals, and/or electromyographic (EMG) signals.

19. A method for processing a physiological signal of interest also comprising unwanted spurious signals, the method comprising:

applying to one or more segments of said physiological signal one or more filters for filtering signal components present in sub-domains of the time/frequency domain plane having a plurality of different shapes,

wherein at least one sub-domain has a shape with a relative temporal duration substantially greater than a relative frequency bandwidth, a relative temporal duration of a shape being a temporal duration of the shape in comparison to the temporal duration of the signal segment being processed, and a relative frequency bandwidth of a shape being a bandwidth of the shape in comparison to the bandwidth of the signal segment being processed, and

wherein at least one sub-domain has a shape with a relative temporal duration substantially less than a relative frequency bandwidth;

20. The method of claim 19 wherein applying a filter further comprises

determining whether signal components present in a time/frequency sub-domain arise from spurious signals, and

limiting said signal components that arise from spurious signals.

21. The method of claim 20 wherein limiting said signal components further comprises setting an amplitude of said signal components to zero.

22. The method of claim 20 wherein limiting said signal components further comprises applying a threshold function to said signal components.

23. The method of claim 20 wherein a signal component present in a time/frequency sub-domain is determined to arise from spurious signals if said signal component has a temporal variation in said sub-domain that is substantially less than the temporal variation of said physiological signal of interest.

24. The method of claim 20 wherein a signal component present in a time/frequency sub-domain is determined to arise from spurious signals if said signal component has characteristics that are statistically distinguishable from said physiological signal of interest.

25. The method of claim 19 wherein applying a filter for filtering signal components present in a time/frequency sub-domain having a shape with a relative temporal duration substantially greater than a relative frequency bandwidth further comprises performing a windowed Fourier transform.

26. The method of claim 19 wherein applying a filter for filtering signal components present in a time/frequency sub-domain having a shape with a relative temporal duration substantially less than a relative frequency bandwidth further comprises performing a wavelet transform.

27. The method of claim 19 wherein applying said filters further comprises applying said filters in a temporal sequence.

28. The method of claim 19 wherein said physiological signals comprise one or more of electroencephalographic (EEG) signals, and/or electrooculographic (EOG) signals, and/or electromyographic (EMG) signals, and/or electrocardiographic (ECG) signals.

29. The method of claim 19 wherein the relative temporal duration of at least one sub-domain is greater than or equal to approximately five times the relative frequency bandwidth of that sub-domain.

30. The method of claim 19 wherein the relative temporal duration of at least one sub-domain is less than or equal to approximately two times the relative frequency bandwidth of that sub-domain.

31. A computer system for processing a physiological signal of interest also comprising unwanted spurious signals, the system comprising a computer readable memory comprising encoded instructions for causing a processor to perform the steps of

limiting at least one narrow-band spurious signal by

performing one or more windowed Fourier transforms on one or more segments of said physiological signal, and

filtering Fourier coefficients having temporal variation substantially less than the temporal variation of said physiological signal and having relative temporal duration substantially greater than relative frequency bandwidth, a relative temporal duration being a temporal duration in comparison to the temporal duration of the signal segment being processed, and a relative frequency bandwidth being a bandwidth in comparison to the bandwidth of the signal segment being processed;

and

limiting at least one intermittently-occurring spurious signal by

performing one or more wavelet transforms on one or more segments of said physiological signal, and

filtering wavelet coefficients having characteristics that are distinguishable from said physiological signal of interest and having relative temporal duration substantially less than relative frequency bandwidth.

32. A computer readable memory for processing a physiological signal of interest also comprising unwanted spurious signals, the memory comprising encoded instructions for causing a processor to perform the steps of

limiting at least one narrow-band spurious signal by

performing one or more windowed Fourier transforms on one or more segments of said physiological signal, and

filtering Fourier coefficients having temporal variation substantially less than the temporal variation of said physiological signal and having relative temporal duration substantially greater than relative frequency bandwidth, a relative temporal duration being a temporal duration in comparison to the temporal duration of the signal segment being processed, and a relative frequency bandwidth being a bandwidth in comparison to the bandwidth of the signal segment being processed;

and

limiting at least one intermittently-occurring spurious signal by

performing one or more wavelet transforms on one or more segments of said physiological signal, and

filtering wavelet coefficients having characteristics that are distinguishable from said physiological signal of interest and having relative temporal duration substantially less than relative frequency bandwidth.