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Detecting fatigue thresholds from electromyographic signals: A systematic review on approaches and methodologies
Institution:1. University of Nebraska – Lincoln, Lincoln, NE, United States;2. University of Kansas, Lawrence, KS, United States;3. Creighton University, Omaha, NE, United States;4. University of North Carolina – Chapel Hill, Chapel Hill, NC, United States;5. University of Wisconsin – La Crosse, La Crosse, WI, United States;6. University of Kentucky, Lexington, KY, United States;7. Oklahoma State University – Stillwater, Stillwater, OK, United States;1. Bioengineering and Biomechanics Laboratory, Universidade Federal de Goiás, Goiânia, Brazil;2. Laboratory of Biomedical Engineering, Universidade Federal de Uberlândia, Uberlândia, Brazil;1. Faculty of Health Sciences, University of Ottawa, Ottawa, Canada;2. Faculty of Engineering, University of Ottawa, Ottawa, Canada;1. Department of Kinesiology, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada;2. Faculty of Kinesiology & Physical Education, University of Toronto, Toronto, Ontario M5S 2W6, Canada;3. Department of Research, Canadian Memorial Chiropractic College, North York, Ontario M2H 3J1, Canada
Abstract:
Keywords:Electromyographic threshold  Muscular fatigue  Aerobic-anaerobic transition  Cycling ergometer  Incremental exercise  Constant workload  Review
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