Determining muscle forces of the finger during heavy work is important for an understanding and prevention of tenosynovitis. Electromyography is one index of muscle activity. Measurements by surface electromyography (sEMG) are noninvasive and simple to apply to obtain signals of muscle action potentials. The sEMG potentials of muscles near the electrode are superimposed. To identify the muscle activities from sEMG measurements, it is necessary first to analyze the characteristics of sEMG conduction in the forearm. This paper develops a conduction model of the forearm that incorporates the muscles and the radius and ulna bones. sEMG distributions were analyzed using the finite element method. The Root mean square (RMS) values of sEMG values and the power exponent of the attenuation (PEA) in relation to the length between the electrode and the source of muscle action potential were estimated in this work. Further, the positions of muscle action potential were reverse-estimated using the RMS values and the PEA. As a result, the PEA was found to increase monotonically with increases in the inter-electrode distance (IED) of the surface electrode pair. The errors in the estimated positions of muscle action potential increased with decreases in the distance between the source of muscle action potential and the radius and ulna bones.
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Nakajima, Y., Yoshinari, S., Tadano, S. (2009). Surface Conduction Analysis of EMG Signal from Forearm Muscles. In: Lim, C.T., Goh, J.C.H. (eds) 13th International Conference on Biomedical Engineering. IFMBE Proceedings, vol 23. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92841-6_472
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-92840-9
Online ISBN: 978-3-540-92841-6