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Time Domain Features of Multi-channel EMG Applied to Prediction of Physiological Parameters in Fatiguing Bicycling Exercises., , , и . SCAI, том 278 из Frontiers in Artificial Intelligence and Applications, стр. 118-127. IOS Press, (2015)Fibre type specific increase in passive muscle tension in spinal cord injured subjects with spasticity, , , , , , и . Journal of Physiology, (2006)To Measure or not to measure: Why web usability is different from traditional usability.. WebNet, стр. 425-430. AACE, (2000)Predicting physiological parameters in fatiguing bicycling exercises using muscle activation timing., , , и . Biomed. Signal Process. Control., (2017)A Novel Method for Classification of Running Fatigue Using Change-Point Segmentation., , , , и . Sensors, 19 (21): 4729 (2019)Exploring relations between EMG and biomechanical data recorded during a golf swing., , , и . Expert Syst. Appl., (2017)Predicting Blood Lactate Concentration and Oxygen Uptake from sEMG Data during Fatiguing Cycling Exercise., , , и . Sensors, 15 (8): 20480-20500 (2015)Electromyographic Patterns during Golf Swing: Activation Sequence Profiling and Prediction of Shot Effectiveness., , , , и . Sensors, 16 (4): 592 (2016)Automatic scoring of lateral and sternal lying posture in grouped pigs using image processing and Support Vector Machine., , , , , , и . Comput. Electron. Agric., (2019)Deep Learning and Machine Vision Approaches for Posture Detection of Individual Pigs., , , , , , и . Sensors, 19 (17): 3738 (2019)