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Dexterous prosthetic hands have better grasp performance than traditionalones. However, patients still find it difficult to use these hands without asuitable control system. A new hybrid myoelectric control system, termed i-MYO,is presented and evaluated to solve this problem. The core component of thei-MYO is a novel grasp-type switching interface based on eye-tracking andaugmented reality (AR), termed i-GSI. With the i-GSI, the user can easilyswitch a grasp type (six total) for a prosthetic hand by gazing at aGazeButton. The i-GSI is implemented in an AR helmet and is integrated, as anindividual module, into the i-MYO system. In the i-MYO system, the myoelectricsignal was used to control hand opening /closing proportionally. The operationof the i-MYO was tested on nine healthy subjects who wore HIT-V hand on theforearm and manipulated objects in a reach-and-grasp task. It was also testedon one patient who had an inferior myoelectric signal and was required tocontrol the HIT-V hand to grasp objects. Results showed that in 91.6% of thetrials, inexperienced healthy subjects accomplished the task within 5.9 s, andmost failed trials were caused by a lack of experience in fine grasping. Inaddition, in about 1.5% of trials, the subjects also successfully transferredthe objects but with a non-optimal grasp type. In 97.0% of the trials, thesubjects spent ~1.3 s switching the optimal grasp types. A higher success ratein grasp type (99.1%) for the untrained patient has been observed thanks tomore trials conducted. In 98.7 % of trials, the patient only needed another 2 sto control the hand to grasp the object after switching to the optimal grasptype. The tests demonstrate the control capability of the new system inmulti-DOF prosthetics, and all inexperienced subjects were able to master theoperation of the i-MYO quickly within a few pieces of training and apply iteasily.

i-MYO: A Hybrid Prosthetic Hand Control System based on Eye-tracking, Augmented Reality and Myoelectric signal