NDLI: Frequency tracking and variable bandwidth for line noise filtering without a reference

Content Provider	IEEE Xplore Digital Library
Author	Kelly, J.W. Collinger, J.L. Degenhart, A.D. Siewiorek, D.P. Smailagic, A. Wei Wang
Copyright Year	2011
Description	Author affiliation: Dept. of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213 USA (Degenhart, A.D.) \|\| Dept. of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213 USA (Collinger, J.L.) \|\| Dept. of Physical Medicine and Rehab., University of Pittsburgh, Pittsburgh, PA 15213 USA (Wei Wang) \|\| Dept. of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213 USA (Kelly, J.W.; Siewiorek, D.P.; Smailagic, A.)
Abstract	This paper presents a method for filtering line noise using an adaptive noise canceling (ANC) technique. This method effectively eliminates the sinusoidal contamination while achieving a narrower bandwidth than typical notch filters and without relying on the availability of a noise reference signal as ANC methods normally do. A sinusoidal reference is instead digitally generated and the filter efficiently tracks the power line frequency, which drifts around a known value. The filter's learning rate is also automatically adjusted to achieve faster and more accurate convergence and to control the filter's bandwidth. In this paper the focus of the discussion and the data will be electrocorticographic (ECoG) neural signals, but the presented technique is applicable to other recordings.
Starting Page	7908
Ending Page	7911
File Size	689490
Page Count	4
File Format	PDF
ISBN	9781424441211
ISSN	1557170X
e-ISBN	9781457715891
e-ISBN	9781424441228
DOI	10.1109/IEMBS.2011.6091950
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-08-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bandwidth Adaptive filters IIR filters Band pass filters Signal to noise ratio Frequency measurement notch filter adaptive filter line noise frequency tracking variable bandwidth neural signals
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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