A glove-based system for studying hand-object manipulation via joint pose and force sensing

@article{Liu2017AGS,
  title={A glove-based system for studying hand-object manipulation via joint pose and force sensing},
  author={Hangxin Liu and Xu Xie and Matt Millar and Mark Edmonds and Feng Gao and Yixin Zhu and Veronica J. Santos and Brandon Rothrock and Song-Chun Zhu},
  journal={2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  year={2017},
  pages={6617-6624}
}
We present a design of an easy-to-replicate glove-based system that can reliably perform simultaneous hand pose and force sensing in real time, for the purpose of collecting human hand data during fine manipulative actions. The design consists of a sensory glove that is capable of jointly collecting data of finger poses, hand poses, as well as forces on palm and each phalanx. Specifically, the sensory glove employs a network of 15 IMUs to measure the rotations between individual phalanxes. Hand… CONTINUE READING