Djawad Movafaghian Research Center, Sharif University of Technology, Mechanical Engineering;
Djawad Movafaghian Research Center, Sharif University of Technology, Mechanical Engineering;
Djawad Movafaghian Research Center, Sharif University of Technology, Mechanical Engineering;
Fatigue; Hidden Markov models; Muscles; Artificial neural networks; Electromyography; Frequency-domain analysis; Task analysis;
机译:使用BF-PSO优化多级GP分类来识别导频的疲劳状态,SEMG信号
机译:sEMG信号持续识别双侧肘关节屈伸的初步研究
机译:带有sEMG的镜像运动系统开发用于中风后偏瘫患者的肩膀康复
机译:SEMG信号中行程后康复运动中的疲劳状态识别
机译:运动康复对多发性硬化症疲劳的影响。
机译:sEMG信号持续识别双侧肘关节屈伸的初步研究
机译:利用sEmG信号进行双侧康复持续识别肘关节屈伸的初步研究
机译:从sEmG信号的TF分布评估肌肉疲劳