Conditioning and Sampling Issues of EMG Signals in Motion Recognition of Multifunctional Myoelectric Prostheses
Author:
Publisher
Springer Science and Business Media LLC
Subject
Biomedical Engineering
Link
http://link.springer.com/content/pdf/10.1007/s10439-011-0265-x.pdf
Reference27 articles.
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2. Chan, A. D., and K. B. Englehart. Continuous myoelectric control for powered prostheses using hidden Markov models. IEEE Trans. Biomed. Eng. 52:121–124, 2005.
3. Chu, J. U., I. Moon, and M. S. Mun. A real-time EMG pattern recognition system based on linear-nonlinear feature projection for a multifunction myoelectric hand. IEEE Trans. Biomed. Eng. 53:2232–2239, 2006.
4. Clancy, E. A., S. Bouchard, and D. Rancourt. Estimation and application of EMG amplitude during dynamic contractions. IEEE Eng. Med. Biol. Mag. 20(6):47–54, 2001.
5. Clancy, E. A., E. L. Morin, and R. Merletti. Sampling, noise-reduction and amplitude estimation issues in surface electromyography. J. Electromyogr. Kinesiol. 12:1–16, 2002.
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