DocumentCode :
1213695
Title :
High-Resolution Alignment of Sampled Waveforms
Author :
McGill, Kevin C. ; Dorfman, Leslie J.
Author_Institution :
Department of Neurology, Stanford University School of Medicine, Stanford, CA 94305, and the Rehabilitative Research and Development Center, Palo Alto Veterans Administration Medical Center
Issue :
6
fYear :
1984
fDate :
6/1/1984 12:00:00 AM
Firstpage :
462
Lastpage :
468
Abstract :
Waveforms are often sampled faster than the Nyquist rate to obtain desired temporal resolution, even though, theoretically, oversampling adds no information and should not be necessary. This paper shows how high resolution can be achieved efficiently from data sampled at the Nyquist rate by working with coefficients of the Fourier-series expansion of the continuous interpolating waveform. Practical algorithms are presented for aligning and comparing waveforms, locating peaks, resolving superimpositions, and averaging overlapping waveforms. The algorithms prove to be more accurate, and to require fewer computations and less storage than techniques which employ continuous oversampling in many signal-processing applications, particularly template matching.
Keywords :
Computational efficiency; Digital filters; Electromyography; Low-frequency noise; Noise level; Noise reduction; Sampling methods; Signal resolution; Signal to noise ratio; Thumb; Electromyography; Humans; Information Theory; Motor Neurons;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.1984.325413
Filename :
4121865
Link To Document :
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