Document Detail


An Adaptive Filter for the Removal of Drifting Sinusoidal Noise without a Reference.
MedLine Citation:
PMID:  25474814     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
This paper presents a method for filtering sinusoidal noise with a variable bandwidth filter that is capable of tracking a sinusoid's drifting frequency. The method, which is based on the adaptive noise canceling (ANC) technique, will be referred to here as the adaptive sinusoid canceler (ASC). The ASC eliminates sinusoidal contamination by tracking its frequency and achieving a narrower bandwidth than typical notch filters. The detected frequency is used to digitally generate an internal reference instead of relying on an external one as ANC filters typically do. The filter's bandwidth adjusts to achieve faster and more accurate convergence. In this paper the focus of the discussion and the data is physiological signals, specifically electrocorticographic (ECoG) neural data contaminated with power line noise, but the presented technique could be applicable to other recordings as well. On simulated data, the ASC was able to reliably track the noise's frequency, properly adjust its bandwidth, and outperform comparative methods including standard notch filters and an adaptive line enhancer (ALE). These results were reinforced by visual results obtained from real ECoG data. The ASC showed that it could be an effective method for increasing signal to noise ratio (SNR) in the presence of drifting sinusoidal noise, which is of significant interest for biomedical applications.
Authors:
John Kelly; Daniel Siewiorek; Asim Smailagic; Wei Wang
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2014-12-02
Journal Detail:
Title:  IEEE journal of biomedical and health informatics     Volume:  -     ISSN:  2168-2208     ISO Abbreviation:  IEEE J Biomed Health Inform     Publication Date:  2014 Dec 
Date Detail:
Created Date:  2014-12-4     Completed Date:  -     Revised Date:  2014-12-5    
Medline Journal Info:
Nlm Unique ID:  101604520     Medline TA:  IEEE J Biomed Health Inform     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
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