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Estimation of peroneal and tibial afferent activity from a multichannel cuff placed on the sciatic nerve
Author(s) -
Cheng HangShing,
Ju MingShaung,
Lin ChouChing K.
Publication year - 2005
Publication title -
muscle and nerve
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.025
H-Index - 145
eISSN - 1097-4598
pISSN - 0148-639X
DOI - 10.1002/mus.20404
Subject(s) - sciatic nerve , tibial nerve , afferent , principal component analysis , cuff , sensory system , biomedical engineering , stimulation , medicine , anatomy , computer science , neuroscience , surgery , artificial intelligence , biology
The afferent signals recorded with a multi‐electrode cuff on the sciatic nerve were employed to investigate the possibility of extracting components ascending from the peroneal and tibial nerves. Two methods, an inverse regression model and principal component method, were studied. The parameters of inverse regression model, determined by data collected in semistatic conditions, were validated by data collected in dynamic conditions. The results showed that the regression model, which used only two channels of the sciatic recordings, was sufficient to separate the distal afferent components. The model, at the expense of requiring distal branch recordings for estimating model parameters, yielded better separation than the principal component method. In conclusion, peroneal and tibial afferent activity can be estimated from the sciatic nerve: the principal component method is suitable for applications focused on acquiring afferent information, whereas the inverse regression model is better for applications in which stimulations will be applied to the branches. The estimation technique provides a powerful tool for in vivo investigation of sensory information transmitted in a peripheral nerve and facilitates implementation of advanced functional neuromuscular stimulation systems. Muscle Nerve, 2005