DocumentCode :
1085293
Title :
Determination of nerve conduction velocity distribution from sampled compound action potential signals
Author :
Gu, D. ; Gander, R.E. ; Crichlow, E.C.
Author_Institution :
Div. of Biomed. Eng., Saskatchewan Univ., Saskatoon, Sask., Canada
Volume :
43
Issue :
8
fYear :
1996
Firstpage :
829
Lastpage :
838
Abstract :
The sampled compound action potential (CAP) data sequence was expressed as the circular convolution of the delay sequence and the sampled single fiber action potential (SFAP) data sequence. An algorithm, based on Hirose´s method (1986) was then developed to separate the delay sequence from the sampled CAP data sequence, and the nerve conduction velocity distribution (NCVD) was consequently calculated from the delay sequence. The NCVD was found to be the product of the amplitude of the SFAP and the number of fibers. Simulations show that the estimated results were in good agreement with the calculated results. Experiments were performed on ten sciatic nerves from five bullfrogs (Rana pipens) using two independent variables: interelectrode distance and stimulus current strength. The results estimated from CAP´s recorded under each condition reflect the corresponding feature of NCVD of the condition. The advantage of the technique is to provide detailed information about both slow and fast conducting fibers. This technique also offers the possibility to directly calculate the nerve fiber diameter distribution from the sampled CAP data sequences.
Keywords :
bioelectric potentials; neurophysiology; signal sampling; CAP data sequence; Hirose´s method; Rana pipens; algorithm; bullfrogs; circular convolution; delay sequence; fast conducting fibers; interelectrode distance; nerve conduction velocity distribution; nerve fiber diameter distribution; sampled compound action potential signals; sampled single fiber action potential; sciatic nerves; slow conducting fibers; stimulus current strength; Biomedical engineering; Convolution; Deconvolution; Delay; Diseases; Electrodes; Helium; Iterative algorithms; Nerve fibers; Senior members; Action Potentials; Algorithms; Animals; Computer Simulation; Models, Neurological; Neural Conduction; Rana pipiens; Sciatic Nerve;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/10.508545
Filename :
508545
Link To Document :
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