Authors: Y.C. Wu, J.S. Chen
Addresses: Department of Power Mechanical Engineering, National Tsing-Hua University, Hsinchu, 30013, Taiwan. ' Department of Power Mechanical Engineering, National Tsing-Hua University, Hsinchu, 30013, Taiwan
Abstract: The electromyogram (EMG) is known to be induced by certain muscle contraction. Except for those disabled who totally lost their extremity, surface EMG signals can be measured from the skin surface. Due to this property, EMG can detect the muscle contraction, and thus can be applied to estimate the required torque for orthosis, and it is thus possible to operate the orthosis in real-time by bio-feedback to enhance human|s physical ability instead of using an artificial limb. In this article, firstly, we introduce inverse dynamics and a muscle mechanics model to infer EMG which is related to the knee torque. Secondly, we make use of an adaptive neuro-fuzzy inference system (ANFIS) to establish a model that related EMG and knee torque. Lastly, we will devise an EMG-based bio-feedback lower limb othosis in real-time through several experiments to validate its efficacy.
Keywords: electromyograms; EMG signals; lower limb orthosis; adaptive neuro-fuzzy inference system; ANFIS; mechatronics; neural networks; fuzzy logic; muscle contraction; biofeedback; knee torque; inverse dynamics; muscle mechanics modelling; bioengineering.
International Journal of Mechatronics and Automation, 2011 Vol.1 No.2, pp.112 - 120
Available online: 12 May 2011 *Full-text access for editors Access for subscribers Purchase this article Comment on this article