IEEE Trans Neural Syst Rehabil Eng. 2020 Oct;28(10):2286-2295. doi: 10.1109/TNSRE.2020.3016909. Epub 2020 Aug 17.
While natural movements result from fluid coordination of multiple joints, commercial upper-limb prostheses are still limited to sequential control of multiple degrees of freedom (DoFs), or constrained to move along predefined patterns. To control multiple DoFs simultaneously, a probability-weighted regression (PWR) method has been proposed and has previously shown good performance with intramuscular electromyographic (EMG) sensors. This study aims to evaluate the PWR method for the simultaneous and proportional control of multiple DoFs using surface EMG sensors and compare the performance with a classical direct control strategy. To extract the maximum number of DoFs manageable by a user, a first analysis was conducted in a virtually simulated environment with eight able-bodied and four amputee subjects. Results show that, while using surface EMG degraded the PWR performance for the 3-DoFs control, the algorithm demonstrated excellent achievements in the 2-DoFs case. Finally, the two methods were compared on a physical experiment with amputee subjects using a hand-wrist prosthesis composed of the SoftHand Pro and the RIC Wrist Flexor. Results show comparable outcomes between the two controllers but a significantly higher wrist activation time for the PWR method, suggesting this novel method as a viable direction towards a more natural control of multi-DoFs.
虽然自然运动是多个关节流畅协调的结果，但商业上肢假肢仍然仅限于多个自由度（DoF）的顺序控制，或者只能沿着预设的模式移动。为了同时控制多个自由度，已经提出了一种概率加权回归（PWR）方法，该方法以前使用肌内电（EMG）传感器显示出良好的性能。本研究旨在使用表面 EMG 传感器评估 PWR 方法用于多自由度的同时和比例控制，并将性能与经典的直接控制策略进行比较。为了从用户那里提取可管理的最大自由度数量，首先在一个具有 8 个健全人和 4 个截肢者的虚拟模拟环境中进行了分析。结果表明，虽然使用表面 EMG 会降低 3-DoF 控制的 PWR 性能，但该算法在 2-DoF 情况下表现出色。最后，在使用 SoftHand Pro 和 RIC Wrist Flexor 组成的手腕假肢的截肢者物理实验中比较了两种方法。结果表明两种控制器的结果相当，但 PWR 方法的手腕激活时间明显更高，这表明这种新方法是一种更自然的多自由度控制的可行方向。
