Methods and systems to quantify and remove asynchronous noise in biophysical signals

Abstract

The exemplified methods and systems described herein facilitate the quantification and/or removal of asynchronous noise, such as muscle artifact noise contamination, to more accurately assess complex nonlinear variabilities in quasi-periodic biophysical-signal systems such as those in acquired cardiac signals, brain signals, etc.

1 . A method to filter asynchronous noise from an acquired biophysical-signal data set, the method comprising:
 receiving, by a processor, a biophysical-signal data set of a subject;   determining, by the processor, at least one template-signal vector data set characteristic of a representative quasi-periodic signal pattern of the subject from a plurality of detected quasi-periodic cycles detected in the received biophysical-signal data set;   applying, by the processor, the at least one determined template-signal vector data set to one or more denoising vector data sets,; and   generating a filtered biophysical-signal data set of the biophysical-signal data set, or a portion thereof, by merging the portion of the received biophysical-signal data set to be filtered and the one or more generated denoising vector data sets.   
     
     
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