Title: Pinpointed muscle force control via optimising human motion and external force

Authors: Ming Ding; Kotaro Hirasawa; Yuichi Kurita; Hiroshi Takemura; Hiroshi Mizoguchi; Jun Takamatsu; Tsukasa Ogasawara

Addresses: RIKEN-TRI Collaboration Centre for Human-Interactive Robot Research, Advanced Science Institute, RIKEN 2271-130, Anagahora, Shimoshidami, Moriyama-ku, Nagoya, Aichi 463-0003, Japan. ' Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama, Ikoma, Nara, 630-0192, Japan. ' Department of System Cybernetics, Faculty of Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima, Hiroshima, 739-8527 Japan. ' Department of Mechanical Engineering, Faculty of Science and Technology, Tokyo University of Science, 2641 Nozaki, Noda, Chiba, 278-8510, Japan. ' Department of Mechanical Engineering, Faculty of Science and Technology, Tokyo University of Science, 2641 Nozaki, Noda, Chiba, 278-8510, Japan. ' Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama, Ikoma, Nara, 630-0192, Japan. ' Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama, Ikoma, Nara, 630-0192, Japan

Abstract: The main focus of our research is to control the load of selected muscles by using a power-assisting device, thus enabling more effective motion support, rehabilitation and training by explicitly specifying the target muscles. In our past research, a control method was proposed for static human motion. The results of simulation and experiments showed that it is possible to control the force of selected muscle individually. However, the past method we proposed was only considered for constant posture, which led to a large effect of non-target muscle. In this paper, a new pinpointed muscle force control method is proposed to reduce the effect of non-target muscle taking into account human motion and external force. Human motion and external force was optimised individually in a double-loop searching algorithm, which reduced the computational cost. By calculating the posture step by step, this method can also be used for quasi-static motion. The validity of this method was confirmed by measuring surface EMG signals for each muscle.

Keywords: musculoskeletal models; rehabilitation; human motion generation; mechatronics; automation; muscle force control; external force; modelling; power-assisting devices; pinpointed muscles; non-target muscles; EMG signals; electromyograms; individual muscles; single muscles; muscle control; muscle assistance; muscle support.

DOI: 10.1504/IJMA.2012.049389

International Journal of Mechatronics and Automation, 2012 Vol.2 No.3, pp.147 - 156

Received: 25 Mar 2011
Accepted: 21 Apr 2012
Published online: 27 Nov 2014 *

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