The New Jersey Institute of Technology's
Electronic Theses & Dissertations Project

Title:	Application of signal processing techniques for measurement of muscle fiber conduction velocity
Author:	Swaminathan, Satheesh Kumar
View Online:	njit-etd1995-016 (xvii, 131 pages ~ 5.3 MB pdf)
Department:	Biomedical Engineering Committee
Degree:	Master of Science
Program:	Biomedical Engineering
Document Type:	Thesis
Advisory Committee:	Reisman, Stanley S. (Committee chair) Kristol, David S. (Committee member) Findley, Thomas W. (Committee member)
Date:	1995-05
Keywords:	Muscles--Physiology Singal processing Muscles--Fatigue--Testing
Availability:	Unrestricted
Abstract:	The objectives of this study were to evaluate if muscle fiber conduction velocity (MFCV) could be used as a reliable indicator of fatigue and to characterize the recovery of MFCV after a fatiguing contraction. The decline of MFCV with fatigue was modelled using linear regression and compared with the decline in median frequency (MF). It was found that the percent decline in MF with fatigue was greater than that of MFCV with fatigue and that the decline of MFCV was consistent in all subjects tested. It was thus determined that MFCV could be used as a reliable indicator of fatigue. Possible explanations for the recovery of MFCV after fatigue were given. The recovery curves for all subjects were curve fit using the exponential peeling technique. A comparison of the time constants showed that 8 out of 9 subjects had values between 2-4 minutes, indicating that the recovery process had a similar response in these 8 subjects. Decomposition of the EMG is a useful tool which helps us better understand the functioning of the neuromuscular system. An algorithm was developed to decompose the EMG into its constituent motor units based on the work done by Deluca et al. Preliminary results were obtained. However, further research is needed in this area.