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JRM Vol.17 No.6 pp. 617-627
doi: 10.20965/jrm.2005.p0617
(2005)

Paper:

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Spinal Information Processing and its Application to Motor Learning Support

Mihoko Otake*,**, and Yoshihiko Nakamura***

*Division of Project Coordination, University of Tokyo, 5-1-5 Kashiwa-no-ha, Kashiwa, Chiba 277-8568, Japan

**PRESTO program, Japan Science and Technology Agency

***Graduate School of Information Science and Technology, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan

Received:
January 28, 2005
Accepted:
June 14, 2005
Published:
December 20, 2005
Creative Commons License
Keywords:
motor learning, muscle innervation, simulation, spinal cord, human behavior analysis
Abstract
We designed motor learning support for acquiring motor skills involving neural mechanisms. We should be able to acquire neural information by analyzing whole-body muscle data, because the nervous system controls the musculoskeletal system and lengths and forces information is fed back to the nervous system. Motor information is calculated by mapping motion-capture data on to a musculoskeletal human model. Neural information represents the set of motor information on the muscles innervated by the arbitrary spinal cord segment. Neural information processing is proposed which calculates correlation among the neural information. We demonstrate the effectiveness of our proposal by experimental results of “kesagiri.”
Cite this article as:
M. Otake and Y. Nakamura, “Spinal Information Processing and its Application to Motor Learning Support,” J. Robot. Mechatron., Vol.17 No.6, pp. 617-627, 2005.
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