Pistohl Tobias, Joshi Deepak, Ganesh Gowrishankar, Jackson Andrew, Nazarpour Kianoush
IEEE Trans Neural Syst Rehabil Eng. 2015 May;23(3):498-507. doi: 10.1109/TNSRE.2014.2355856. Epub 2014 Sep 9.
The typical control of myoelectric interfaces, whether in laboratory settings or real-life prosthetic applications, largely relies on visual feedback because proprioceptive signals from the controlling muscles are either not available or very noisy. We conducted a set of experiments to test whether artificial proprioceptive feedback, delivered noninvasively to another limb, can improve control of a two-dimensional myoelectrically-controlled computer interface. In these experiments, participants were required to reach a target with a visual cursor that was controlled by electromyogram signals recorded from muscles of the left hand, while they were provided with an additional proprioceptive feedback on their right arm by moving it with a robotic manipulandum. Provision of additional artificial proprioceptive feedback improved the angular accuracy of their movements when compared to using visual feedback alone but did not increase the overall accuracy quantified with the average distance between the cursor and the target. The advantages conferred by proprioception were present only when the proprioceptive feedback had similar orientation to the visual feedback in the task space and not when it was mirrored, demonstrating the importance of congruency in feedback modalities for multi-sensory integration. Our results reveal the ability of the human motor system to learn new inter-limb sensory-motor associations; the motor system can utilize task-related sensory feedback, even when it is available on a limb distinct from the one being actuated. In addition, the proposed task structure provides a flexible test paradigm by which the effectiveness of various sensory feedback and multi-sensory integration for myoelectric prosthesis control can be evaluated.
无论是在实验室环境还是实际的假肢应用中,肌电接口的典型控制在很大程度上依赖于视觉反馈,因为来自控制肌肉的本体感觉信号要么无法获取,要么噪声很大。我们进行了一系列实验,以测试非侵入性地传递到另一肢体的人工本体感觉反馈是否能改善二维肌电控制计算机接口的控制效果。在这些实验中,参与者需要用由左手肌肉记录的肌电图信号控制的视觉光标到达目标,同时通过机器人操作器移动右臂为他们提供额外的本体感觉反馈。与仅使用视觉反馈相比,提供额外的人工本体感觉反馈提高了他们运动的角度准确性,但并没有提高用光标与目标之间的平均距离量化的整体准确性。本体感觉带来的优势仅在本体感觉反馈在任务空间中的方向与视觉反馈相似时才存在,而在镜像时则不存在这表明反馈模式的一致性对于多感官整合至关重要我们的结果揭示了人类运动系统学习新的肢体间感觉运动关联的能力;即使这种感觉反馈来自与被驱动肢体不同的另一肢体,运动系统也可以利用与任务相关的感觉反馈此外所提出的任务结构提供了一种灵活测试范式通过该范式可以评估各种感觉反馈和多感官整合对肌电假肢控制的有效性