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This paper presents analysis and modeling of walking behavior based on a stochastic switched link model. The model of human legs are modeled as a pendulum or an inverted pendulum where the length can be expanded and contracted. In our framework, these primitive models correspond to modes and are supposed to switch stochastically. Then the EM algorithm are applied to derive the parameters in a similar manner with the case for the Hidden Markov Model. For measurement of the behavior, an optical motion capture system is used, and individual identification using gait is verified through the experiments based on the proposed model.

2P1-A13 Modeling and Analysis of Walking Motion based on Stochastic Switched Link Model