Mangezi Andrew, Rosendo Andre, Howard Matthew, Stopforth Riaan
IEEE Int Conf Rehabil Robot. 2017 Jul;2017:1343-1348. doi: 10.1109/ICORR.2017.8009435.
With continuous advancements on active prosthetics the detection of the user's intention becomes the new technological bottleneck. While electromyography (EMG) is widely used to detect individual muscular contributions, sweat and relative sensor movements degrade the quality of the signal over time. In this paper, we bypass the problems created with the skin contact analyzing the muscular activation with Archimedean Spiral (AS) electrodes. We compare traditional EMG electrodes with AS electrodes, stacked up in textile embroidered layers to improve their functionality, and eventually adding a layer of cloth/silicon between the electrodes and the human skin to ascertain the feasibility of the method. We use n=9 volunteers to perform a loaded wrist extension and record signals from the extensor digitorum muscle group. We evaluate the amplitude and noise from all results and conclude that the AS electrode is capable of detecting muscular activation without touching the skin. As part of a low-cost prosthetic initiative, this EMG alternative can be potentially embedded to the prosthetic socket to improve usage and reduce adaptation problems.
随着主动假肢技术的不断进步,用户意图的检测成为了新的技术瓶颈。虽然肌电图(EMG)被广泛用于检测个体肌肉的贡献,但随着时间的推移,汗液和相关传感器的运动会降低信号质量。在本文中,我们通过使用阿基米德螺旋(AS)电极分析肌肉激活情况,绕过了皮肤接触带来的问题。我们将传统的肌电图电极与AS电极进行比较,将它们堆叠在纺织绣花层中以提高其功能,并最终在电极与人体皮肤之间添加一层布/硅来确定该方法的可行性。我们使用n = 9名志愿者进行负重手腕伸展,并记录来自指伸肌肌群的信号。我们评估了所有结果的幅度和噪声,并得出结论,AS电极能够在不接触皮肤的情况下检测肌肉激活。作为低成本假肢计划的一部分,这种肌电图替代方案有可能嵌入到假肢插座中,以改善使用情况并减少适应问题。