DocumentCode
1130431
Title
Action potential classification with dual channel intrafascicular electrodes
Author
McNaughton, Timothy G. ; Horch, Kenneth W.
Author_Institution
Dept. of Bioeng., Utah Univ., Salt Lake City, UT, USA
Volume
41
Issue
7
fYear
1994
fDate
7/1/1994 12:00:00 AM
Firstpage
609
Lastpage
616
Abstract
Using recordings of peripheral nerve activity made with carbon fiber intrafascicular electrodes, the authors compared the performance of three different recording techniques (single channel, differential, and dual channel) and four different unit classification methods (linear discriminant analysis, template matching, a novel time amplitude windowing technique, and neural networks) in terms of errors in waveform classification and artifact rejection. Dual channel recording provided uniformly superior unit separability, neural networks gave the lowest classification error rates, and template matching had the best artifact rejection performance.
Keywords
bioelectric potentials; biological techniques and instruments; medical signal processing; neurophysiology; C; action potential classification; artifact rejection; carbon fiber intrafascicular electrodes; differential recording; dual channel intrafascicular electrodes; dual channel recording; linear discriminant analysis; neural networks; single channel recording; template matching; time amplitude windowing technique; unit classification methods; unit separability; waveform classification errors; Biological neural networks; Biomedical electrodes; Central nervous system; Disk recording; Error analysis; Linear discriminant analysis; Muscles; Nerve fibers; Shape; Skin; Action Potentials; Animals; Axons; Bayes Theorem; Cats; Discriminant Analysis; Electrodes; Equipment Design; Linear Models; Neural Networks (Computer); Peripheral Nerves; Radial Nerve; Signal Processing, Computer-Assisted;
fLanguage
English
Journal_Title
Biomedical Engineering, IEEE Transactions on
Publisher
ieee
ISSN
0018-9294
Type
jour
DOI
10.1109/10.301727
Filename
301727
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