Analysis of collective behavior and grasp motion in human hand

In this paper, we propose a method for analyzing and synthesizing human's grasping motion and the corresponding collective behaviors in the human hand. We apply PCA technique for a dimension reduction and then Gaussian mixture model(GMM) in order to identify the grasp type and the associated object parameters for a given joint data set. We verify the validity of the analysis through simulation with human grasp data captured by a data glove.

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