Intuitive Human-Robot-Environment Interaction With EMG Signals:A Review

A long history has passed since electromyography(EMG)signals have been explored in human-centered robots for intuitive interaction.However,it still has a gap between scientific research and real-life applications.Previous studies mainly focused on EMG decoding algorithms,leaving a dynamic rela-tionship between the human,robot,and uncertain environment in real-life scenarios seldomly concerned.To fill this gap,this paper presents a comprehensive review of EMG-based techniques in human-robot-environment interaction(HREI)systems.The gen-eral processing framework is summarized,and three interaction paradigms,including direct control,sensory feedback,and par-tial autonomous control,are introduced.EMG-based intention decoding is treated as a module of the proposed paradigms.Five key issues involving precision,stability,user attention,compli-ance,and environmental awareness in this field are discussed.Several important directions,including EMG decomposition,robust algorithms,HREI dataset,proprioception feedback,rein-forcement learning,and embodied intelligence,are proposed to pave the way for future research.To the best of what we know,this is the first time that a review of EMG-based methods in the HREI system is summarized.It provides a novel and broader perspective to improve the practicability of current myoelectric interaction systems,in which factors in human-robot interaction,robot-environment interaction,and state perception by human sensations are considered,which has never been done by previ-ous studies.