標題: Upper-Limb EMG-Based Robot Motion Governing Using Empirical Mode Decomposition and Adaptive Neural Fuzzy Inference System
作者: Liu, Hsiu-Jen
Young, Kuu-Young
電子工程學系及電子研究所
電機工程學系
Department of Electronics Engineering and Institute of Electronics
Department of Electrical and Computer Engineering
關鍵字: Electromyography (EMG);Human-assisting robot;Upper-limb motion classification;Empirical mode decomposition (EMD);Adaptive neuro-fuzzy inference system (ANFIS)
公開日期: 1-十二月-2012
摘要: To improve the quality of life for the disabled and elderly, this paper develops an upper-limb, EMG-based robot control system to provide natural, intuitive manipulation for robot arm motions. Considering the non-stationary and nonlinear characteristics of the Electromyography (EMG) signals, especially when multi-DOF movements are involved, an empirical mode decomposition method is introduced to break down the EMG signals into a set of intrinsic mode functions, each of which represents different physical characteristics of muscular movement. We then integrate this new system with an initial point detection method previously proposed to establish the mapping between the EMG signals and corresponding robot arm movements in real-time. Meanwhile, as the selection of critical values in the initial point detection method is user-dependent, we employ the adaptive neuro-fuzzy inference system to find proper parameters that are better suited for individual users. Experiments are performed to demonstrate the effectiveness of the proposed upper-limb EMG-based robot control system.
URI: http://dx.doi.org/10.1007/s10846-012-9677-6
http://hdl.handle.net/11536/20391
ISSN: 0921-0296
DOI: 10.1007/s10846-012-9677-6
期刊: JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
Volume: 68
Issue: 3-4
起始頁: 275
結束頁: 291
顯示於類別:期刊論文


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  1. 000310084800006.pdf