Dynamic Control Of Virtual Hand Grasp Using Spatiotemporal Synergies

Recent advances in assistive hand devices have produced high degree of freedom systems which are capable of complex grasping, however user-friendly control of these sophisticated devices is still an open topic in research. Synergy-based controllers which dimensionally reduced the control problem were present in the literature, however they used spatial/postural synergies which are static over time. In this paper, we proposed the first control system based on spatiotemporal synergies which is scalable to any number of degrees of freedom, any number of synergies, and any duration of synergy. The controller was tested on prior data in which ten subjects performed 50 object grasps and 36 American Sign Language letters and numbers. The tuned response of the controller, the l(1)-norm reconstruction error, and the simulation error were all reported in detail. The angular error between the simulated model and recorded states decayed rapidly from 23.1 +/- 19.98% with the first synergy to 6.18 +/- 8.75% for synergies 1 to 6 and 2.29 +/- 3.35% for synergies 1 to 10 and was statistically similar to the reconstruction error of the angular trajectories. Minor improvements in performance were observed when using higher-order synergies, implying a tradeoff between accuracy and control complexity. The data shown here can be used to select the number of synergies to use in control based on the accuracy of the controller and the accuracy of the controlled robotic system. The resulting system achieved high grasping dexterity with minimal computational or manual effort for assistive devices.