Synergy-Based Hand Pose Sensing: Optimal Glove Design

In this paper we study the problem of optimally designing glove–based sensing devices for hand pose reconstruction to maximize their potential for precision. In a companion paper we studied the problem of maximizing the reconstruction accuracy of the hand pose from partial and noisy data provided by any given pose sensing device (a sensorized “glove”) taking into account the knowledge on how humans most frequently use their hands in grasping tasks. In this paper we consider the dual problem of how to design pose sensing devices, i.e. how and where to place sensors on a glove, to get maximum information about the actual hand posture. We study the optimal design of gloves of different nature, according to a classification of current sensing technologies adopted in the domain. The objective is to provide, for given a priori information and fixed number of sensor inputs, the optimal design minimizing the reconstruction error statistics (assuming that optimal reconstruction algorithms are adopted). Finally, an experimental evaluation of the proposed method for optimal design is provided.