i‐MYO: A multi‐grasp prosthetic hand control system based on gaze movements, augmented reality, and myoelectric signals

Abstract Background Controlling a multi‐grasp prosthetic hand still remains a challenge. This study explores the influence of merging gaze movements and augmented reality in bionics on improving prosthetic hand control. Methods A control system based on gaze movements, augmented reality, and myoelectric signals (i‐MYO) was proposed. In the i‐MYO, the GazeButton was introduced into the controller to detect the grasp‐type intention from the eye‐tracking signals, and the proportional velocity scheme based on the i‐MYO was used to control hand movement. Results The able‐bodied subjects with no prior training successfully transferred objects in 91.6% of the cases and switched the optimal grasp types in 97.5%. The patient could successfully trigger the EMG to control the hand holding the objects in 98.7% of trials in around 3.2 s and spend around 1.3 s switching the optimal grasp types in 99.2% of trials. Conclusions Merging gaze movements and augmented reality in bionics can widen the control bandwidth of prosthetic hand. With the help of i‐MYO, the subjects can control a prosthetic hand using six grasp types if they can manipulate two muscle signals and gaze movement.