Abstract
We propose a new surface electromygram (EMG) amplitude estimator, inspired by mechanical behavior of the muscle and characteristics of sEMG recordings. A morphological feature extraction algorithm was implemented to detect motor unit action potentials (MUAPs) from sEMG, and the MUAPs were transformed into the impulse trains. The trains were convoluted with a mathematical function of the muscle twitch model, so that the resultant output represented the muscle activities. Signal to noise ratio (SNR) of the proposed estimator was compared to it of conventional estimation methods such as MAV and RMS, and the proposed estimator provides better SNR in a range of acceptable time delays. This estimator might provide a better analysis tool for quantitative measurement of muscle activities in a large of research areas such as physiology, neuroscience, ergonomics, and biomedical engineering.
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© 2009 Springer-Verlag Berlin Heidelberg
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Choi, C., Kim, J. (2009). Development of a New Surface EMG Amplitude Estimator and the SNR Performance Evaluation Study. In: Dössel, O., Schlegel, W.C. (eds) World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany. IFMBE Proceedings, vol 25/4. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03882-2_38
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DOI: https://doi.org/10.1007/978-3-642-03882-2_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03881-5
Online ISBN: 978-3-642-03882-2
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