Experimental Evaluation of Balance Prediction Models for Sit-to-Stand Movement in the Sagittal Plane

Author:

Pena Cabra Oscar David1,Watanabe Takashi2

Affiliation:

1. Graduate School of Engineering, Tohoku University, Aramaki-aza-Aoba 6-6-11-901-7, Aoba-ku, Sendai 980-8579, Japan

2. Graduate School of Biomedical Engineering, Tohoku University, Aramaki-aza-Aoba 6-6-11-901-7, Aoba-ku, Sendai 980-8579, Japan

Abstract

Evaluation of balance control ability would become important in the rehabilitation training. In this paper, in order to make clear usefulness and limitation of a traditional simple inverted pendulum model in balance prediction in sit-to-stand movements, the traditional simple model was compared to an inertia (rotational radius) variable inverted pendulum model including multiple-joint influence in the balance predictions. The predictions were tested upon experimentation with six healthy subjects. The evaluation showed that the multiple-joint influence model is more accurate in predicting balance under demanding sit-to-stand conditions. On the other hand, the evaluation also showed that the traditionally used simple inverted pendulum model is still reliable in predicting balance during sit-to-stand movement under non-demanding (normal) condition. Especially, the simple model was shown to be effective for sit-to-stand movements with low center of mass velocity at the seat-off. Moreover, almost all trajectories under the normal condition seemed to follow the same control strategy, in which the subjects used extra energy than the minimum one necessary for standing up. This suggests that the safety considerations come first than the energy efficiency considerations during a sit to stand, since the most energy efficient trajectory is close to the backward fall boundary.

Funder

Ministry of Education, Culture, Sports, Science and Technology of Japan

Publisher

Hindawi Limited

Subject

Applied Mathematics,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,Modelling and Simulation,General Medicine

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