Review of electroencephalography and electromyography research in robotics: opportunities and challenges.

IF 6 4区 计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Zefeng Wang, Meiyan Xu, Junfeng Yao, Yue Yu, Bingbing Hu, Yufei Wang, Yu Wang, Xiaopeng Zhang
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引用次数: 0

Abstract

In the evolving nexus of neuroscience and robotics, the symbiotic fusion of electroencephalography (EEG) and electromyography (EMG) is emerging as a paradigm-shifting avenue for enhancing human-machine interfaces. While EEG, which captures the subtle electrical nuances of the brain, offers a potent channel for nuanced brain-machine communication, EMG serves as a bridge, converting neuromuscular intentions into actionable directives for robotic apparatuses. This review highlights the current methodologies in which EEG and EMG not only function in silos but also converge harmoniously to dictate robotic control. By delving deeper into this, the intricate synergy between cognitive processes, muscular responses, and machine actions can be unraveled. Subsequently, the discourse also navigates through the myriad challenges encountered in realizing real-time, seamless integration of these bio-signals with robotics and the innovative solutions poised to address them. The aim is to provide a comprehensive understanding of the interplay between neuroscience and robotics. This insight will help drive breakthroughs in adaptive human-machine collaboration.

机器人脑电图与肌电图研究综述:机遇与挑战。
在神经科学和机器人技术不断发展的联系中,脑电图(EEG)和肌电图(EMG)的共生融合正在成为增强人机界面的范式转变途径。脑电图(EEG)捕捉到大脑细微的电差别,为细致的脑机交流提供了一个强有力的渠道,肌电图(EMG)则充当了一个桥梁,将神经肌肉的意图转化为机器人设备可操作的指令。这篇综述强调了目前的方法,其中脑电图和肌电图不仅在孤岛中发挥作用,而且还协调地收敛以指示机器人控制。通过深入研究,认知过程、肌肉反应和机器动作之间复杂的协同作用可以被解开。随后,讨论还通过实现这些生物信号与机器人的实时无缝集成以及准备解决这些问题的创新解决方案所遇到的无数挑战进行导航。目的是提供对神经科学和机器人之间相互作用的全面理解。这种见解将有助于推动自适应人机协作的突破。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
5.60
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0.00%
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