Method for detecting bio signal features in the presence of noise
AssigneeAir Products and Chemicals, Inc.
InventorsMichael S. Toth, Cecilia Anna Paulette Petit
Life of this patent
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Abstract
A computer-based method for detecting features in a digitally sampled biological (bio) signal includes the steps of applying a wavelet transform to the bio signal to generate a list of wavelet transform coefficients, ranking the coefficients according to value or frequency, and removing at least one low value or low frequency coefficient. The method further includes the steps of performing an inverse wavelet transform using the remaining coefficients to generate a reconstructed signal, and detecting feature locations using the reconstructed signal.
Claims33
A computer-based method for detecting features in a digitally sampled biological (bio) signal, comprising:
- applying a wavelet transform to the bio signal to generate a list of wavelet transform coefficients;
- ranking the coefficients according to value;
- removing at least one low value coefficient;
- performing an inverse wavelet transform using the remaining coefficients to generate a reconstructed signal;
- and
- detecting feature locations using the reconstructed signal.
A computer-based method for detecting features in a digitally sampled biological (bio) signal, comprising:
- applying a wavelet transform to the bio signal to generate a list of wavelet transform coefficients;
- ranking the coefficients according to frequency;
- removing at least one low frequency coefficient;
- performing an inverse wavelet transform using the remaining coefficients to generate a reconstructed signal;
- and
- detecting feature locations using the reconstructed signal.
A device for detecting features in a digitally sampled biological (bio) signal, comprising:
- a communications arrangement configured to receive the bio signal;
- a processor;
- and
- a memory including instructions configuring the processor to:
- apply a wavelet transform to the bio signal to generate a list of wavelet transform coefficients;
- rank the coefficients according to value;
- remove at least one low value coefficient;
- perform an inverse wavelet transform using the remaining coefficients to generate a reconstructed signal;
- and
- detect feature locations using the reconstructed signal.
A device for detecting features in a digitally sampled biological (bio) signal, comprising:
- a communications arrangement configured to receive the bio signal;
- a processor;
- and
- a memory including instructions configuring the processor to:
- apply a wavelet transform to the bio signal to generate a list of wavelet transform coefficients;
- rank the coefficients according to frequency;
- remove at least one low frequency coefficient;
- perform an inverse wavelet transform using the remaining coefficients to generate a reconstructed signal;
- and
- detect feature locations using the reconstructed signal.
A computer-readable medium having stored thereon a series of instructions executable by a processor for detecting features in a digitally sampled biological (bio) signal, the instructions configured to cause the processor to perform the steps of:
- applying a wavelet transform to the bio signal to generate a list of wavelet transform coefficients;
- ranking the coefficients according to value;
- removing at least one low value coefficient;
- performing an inverse wavelet transform using the remaining coefficients to generate a reconstructed signal;
- and
- detecting feature locations using the reconstructed signal.
A computer-readable medium having stored thereon a series of instructions executable by a processor for detecting features in a digitally sampled biological (bio) signal, the instructions configured to cause the processor to perform the steps of:
- applying a wavelet transform to the bio signal to generate a list of wavelet transform coefficients;
- ranking the coefficients according to frequency;
- removing at least one low frequency coefficient;
- performing an inverse wavelet transform using the remaining coefficients to generate a reconstructed signal;
- and
- detecting feature locations using the reconstructed signal.
Dependencies are inferred from the claim text.