Vision-Based Assistance for Myoelectric Hand Control
Vision-Based Assistance for Myoelectric Hand Control
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DOI：
10.1109/access.2020.3036115
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发表时间：
2020-01-01
期刊：
影响因子：
3.9
通讯作者：
Okumura, Hiroshi
中科院分区：
文献类型：
--
作者：
He, Yunan;Kubozono, Ryusuke;Okumura, Hiroshi
传统的假手控制系统使用肌电信号作为接口，但仅凭肌电信号是不可能实现复杂灵活的人手运动的。一种很有前途的假手控制方案使用计算机视觉来帮助抓取物体。它以成像传感器为特色，控制系统能够识别放置在环境中的物体。然后，可以根据识别的对象从一些预定义的候选中选择抓取图案。然而，以往的研究假设环境中只有一个物体存在。如果环境中有多个目标对象，则手在尝试寻找目标对象时可能会变得混乱。本研究针对这一问题，提出了一种从多个目标中确定目标目标的方法。该方法能够通过估计假手与物体之间的位置关系以及手的运动来确定目标物体。为了验证该方法的有效性和有效性，我们在一个基于视觉的假手控制系统中实现了该方法，并进行了拾取放置实验。实验证明，该方法能够准确地估计出符合用户意图的目标对象。
Conventional control systems for prosthetic hands use myoelectric signals as an interface, but it is impossible to realize complex and flexible human hand movements with only myoelectric signals. A promising control scheme for prosthetic hands uses computer vision to assist in grasping objects. It features an imaging sensor, and the control system is capable of recognizing an object placed in the environment. Then, a gripping pattern can be selected from some predefined candidates according the recognized object. However, previous studies assumed that only one object exists in the environment. If there are multiple target objects in the environment, the hand could become confused in attempting to find the target object. This study addresses this problem and proposes a method to determine the target object from multiple objects. The proposed method is able to determine the target object by estimating the positional relationship between the artificial hand and the objects, as well as the motion of the hand. To verify the validity and effectiveness, we implemented the proposed method in a vision-based prosthetic hands control system and conducted pick-and-place experiments. The experiments confirm that the proposed method can accurately estimate the target object in accordance with the user's intention.