State Key Laboratory of Robotics and System, Harbin Institute of Technology (HIT), Harbin, China.
Artificial Intelligence Laboratory (HIT), Harbin, China.
Int J Med Robot. 2024 Feb;20(1):e2617. doi: 10.1002/rcs.2617.
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.
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.
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.
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.
控制多指假肢仍然具有挑战性。本研究探讨了仿生学中融合眼球运动和增强现实技术对改善假肢手控制的影响。
提出了一种基于眼球运动、增强现实和肌电信号（i-MYO）的控制系统。在 i-MYO 中，引入了 GazeButton 来从眼动跟踪信号中检测抓握类型意图，并且使用基于 i-MYO 的比例速度方案来控制手的运动。
未经训练的健全受试者在 91.6%的情况下成功转移了物体，并在 97.5%的情况下切换了最佳抓握类型。患者可以在大约 3.2 秒内成功触发肌电信号来控制握住物体的手，并且在 99.2%的情况下切换最佳抓握类型大约需要 1.3 秒。
仿生学中融合眼球运动和增强现实技术可以拓宽假肢手的控制带宽。借助 i-MYO，如果受试者可以操纵两个肌肉信号和眼球运动，他们可以使用六种抓握类型来控制假肢手。
