NDLI: Convergence characteristics of two algorithms in non-linear stimulus artefact cancellation for electrically evoked potential enhancement

Content Provider	Springer Nature Link
Author	Parsa, V. Parker, P. Scott, R.
Copyright Year	1998
Abstract	Somatosensory evoked potentials (SEPs) are a sub-class of evoked potentials (EPs) that are very useful in diagnosing various neuromuscular disorders and in spinal cord and peripheral-nerve monitoring. Most often, the measurements of these signals are contaminated by stimulus-evoked artefact. Conventional stimulus-artifact (SA) reduction schemes are primarily hardware-based and rely on some form of input blanking during the SA phase. This procedure can result in partial SEP loss if the tail of the SA interferes with the SEP. Adaptive filters offer an attractive solution to this problem by iteratively reducing the SA waveform while leaving the SEP intact. Owing to the inherent non-linearities in the SA generation system, non-linear adaptive filters (NAFs) are most suitable. SA reduction using NAFs based on truncated second-order Volterra expansion series is investigated. The focus is on the performance of two main adaptation algorithms, the least mean square (LMS) and recursive least squares (RLS) algorithms, in the context of non-linear adaptive filtering. A comparison between the convergence and performance characteristics fo these two algorithms is made by processing both simulated and experimental SA data. It is found that, in high artefact-to-noise ratio (ANR) SA cancellation, owing to the large eigenvalue spreads, the RLS-based NAF is more efficient than the LMS-based NAF. However, in low-ANR scenarios, the RLS-and LMS-based NAFs exhibit similar convergence properties, and the computatioal simplicity of the LMS-based NAFs makes them the preferred option.
Starting Page	202
Ending Page	214
Page Count	13
File Format	PDF
ISSN	01400118
Journal	Medical and Biological Engineering and Computing
Volume Number	36
Issue Number	2
e-ISSN	17410444
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	1998-01-01
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Stimulus artefact Artefact reduction SEP signal processing Non-linear adaptive filtering Adaptive Volterra filtering Human Physiology Neurosciences Imaging Radiology Computer Applications Biomedical Engineering
Content Type	Text
Resource Type	Article
Subject	Biomedical Engineering Computer Science Applications

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