DocumentCode :
471597
Title :
Vibromyographic Quantification of Voluntary Isometric Contractile Force in the Brachioradialis
Author :
Cole, Jason P. ; Madhavan, Guruprasad ; McLeod, Kenneth J.
Author_Institution :
Dept. of Bioeng., State Univ. of New York, Binghamton, NY
fYear :
2006
fDate :
Aug. 30 2006-Sept. 3 2006
Firstpage :
1708
Lastpage :
1710
Abstract :
This study investigated the ability of vibromyography (VMG) to accurately represent voluntary forearm muscle contractile force during attempted-isometric contraction of the brachioradialis. VMG signals were collected from the brachioradialis of healthy adult men (mean age, 26.6plusmn9.8 years, N=24) during attempted-isometric contraction over a force range of 4.45 N to maximum sustained load. The VMG signals were decomposed using wavelet packet analysis techniques, and the corresponding wavelet packets were utilized in a multiple regression model for parameter reduction and identification of signal components which best correlated to muscle force. It was observed that just two wavelet components were sufficient to accurately predict muscle force (R 2=0.984, P<0.0001). The signal force relationship observed is monotonic, though quadratic in form. More importantly, the wavelet data was able to predict absolute force output of the brachioradialis without normalization or prior knowledge of a subject´s maximum voluntary force. These data show that VMG recordings are capable of providing a monotonic relationship between VMG signal and muscle force. Moreover, in contrast to EMG technology which can only provide relative force levels, VMG appears to be capable of reporting absolute force levels, an observation which is expected to lead to numerous applications in medicine and rehabilitation
Keywords :
biomechanics; biomedical measurement; electromyography; force measurement; regression analysis; wavelet transforms; attempted-isometric contraction; brachioradialis; electromyography; healthy adult men; mechanomyography; multiple regression model; muscle force measurement; parameter identification; parameter reduction; vibromyography; voluntary forearm muscle contractile force; wavelet packet analysis techniques; Bone diseases; Elbow; Electromyography; Force measurement; Muscles; Protocols; Signal processing; Skin; Wavelet analysis; Wavelet packets; Electromyography; Mechanomyography; Muscle Force Measurement; Vibromyography; Wavelet Analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
Conference_Location :
New York, NY
ISSN :
1557-170X
Print_ISBN :
1-4244-0032-5
Electronic_ISBN :
1557-170X
Type :
conf
DOI :
10.1109/IEMBS.2006.260152
Filename :
4462101
Link To Document :
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