首页|Reports on Robotics Findings from Chinese Academy of Sciences Provide New Insigh ts (Intuitive Human-robot-environment Interaction With Emg Signals: a Review)
Reports on Robotics Findings from Chinese Academy of Sciences Provide New Insigh ts (Intuitive Human-robot-environment Interaction With Emg Signals: a Review)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Robotics have been published. According to news originating from Shenyang, People’s Republic of China, by NewsRx correspondents, research stated, “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 resea rch and real-life applications.” Financial support for this research came from National Key Research and Developm ent Program of China. Our news journalists obtained a quote from the research from the Chinese Academy of Sciences, “Previous studies mainly focused on EMG decoding algorithms, leavi ng a dynamic relationship 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 interac tion (HREI) systems. The general processing framework is summarized, and three i nteraction paradigms, including direct control, sensory feedback, and partial au tonomous control, are introduced. EMG-based intention decoding is treated as a m odule of the proposed paradigms. Five key issues involving precision, stability, user attention, compliance, and environmental awareness in this field are discu ssed. Several important directions, including EMG decomposition, robust algorith ms, HREI dataset, proprioception feedback, reinforcement learning, and embodied intelligence, are proposed to pave the way for future research. To the best of w hat we know, this is the first time that a review of EMG-based methods in the HR EI system is summarized.”
ShenyangPeople’s Republic of ChinaAs iaEmerging TechnologiesMachine LearningRobotRoboticsChinese Academy of Sciences
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