结合计算机视觉、眼动追踪、肌电图和IMU控制灵巧假手的新方法

Chunyuan Shi, Le Qi, Dapeng Yang, Jingdong Zhao, Hong Liu
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引用次数: 6

摘要

传统的肌电控制方法由于鲁棒性差、不稳定、使用负担大,在灵巧假手的控制面前仍然显得力不胜任。为了解决这一问题,本文提出了一种将计算机视觉、眼动追踪、肌电图和IMU相结合的CVEEI方法。首先,通过屏幕前的凝视(眼球追踪),将物体的抓取模式反馈给假手控制器;然后,在肌电图和IMU的协同作用下,可以控制假手将物体运送到预期的位置。在此过程中,计算机视觉可以实时识别所有物体的抓取模式。重要的是,本文通过对比传统的肌电控制方法(共收缩切换)在物体搬运实验中的表现,进一步验证了该方法在灵巧假手操作中的优越性(快速> 1s/单物体)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Novel Method of Combining Computer Vision, Eye-Tracking, EMG, and IMU to Control Dexterous Prosthetic Hand
Due to poor robustness, instability, and the heavy burden of use, the traditional myoelectric control method is still powerless in the face of the control of the dexterous prosthetic hand. To solve this problem, a new method (CVEEI), that combines computer vision, eye tracking, electromyogram (EMG) and IMU was proposed in this paper. Firstly, through gazing (eye-tracking) in front of the screen, the grasping pattern of the objects can be fed back to the prosthetic hand controller; Then, the prosthetic hand can be controlled to transport the object to the position expected, on collaboration of both EMG and IMU. In this process, the grasping pattern of all objects can be recognized by computer vision in real-time. Importantly, through comparing the traditional EMG control method (co-contraction to switch) in the transport experiment of the objects, the superiority of this new method in operating the dexterous prosthetic hand was further verified (fast > 1s/single object) in this paper.
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