Fuzzy Approximate Entropy Analysis of Chaotic and Natural Complex Systems: Detecting Muscle Fatigue Using Electromyography Signals
Author:
Publisher
Springer Science and Business Media LLC
Subject
Biomedical Engineering
Link
http://link.springer.com/content/pdf/10.1007/s10439-010-9933-5.pdf
Reference47 articles.
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2. Bilodeau, M., S. Schindler-Ivens, D. M. Williams, R. Chandran, and S. S. Sharma. EMG frequency content changes with increasing force and during fatigue in the quadriceps femoris muscle of men and women. J. Electromyogr. Kinesiol. 13:83–92, 2003.
3. Bonato, P. Recent advancements in the analysis of dynamic EMG data. IEEE Med. Biol. Mag. 20(6):29–32, 2001.
4. Bonato, P., S. H. Roy, M. Knaflitz, and C. J. De Luca. Time-frequency parameters of the surface myoelectric signal for assessing muscle fatigue during cyclic dynamic contractions. IEEE Trans. Biomed. Eng. 48:745–753, 2001.
5. Caldirola, D., L. Bellodi, A. Caumo, G. Migliarese, and G. Perna. Approximate entropy of respiratory patterns in panic disorder. Am. J. Psychiatr. 161:79–87, 2004.
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