IEEE Trans Neural Syst Rehabil Eng. 2022;30:893-904. doi: 10.1109/TNSRE.2022.3163149. Epub 2022 Apr 11.
Recent research has advanced two degree-of-freedom (DoF), simultaneous, independent and proportional control of hand-wrist prostheses using surface electromyogram signals from remnant muscles as the control input. We evaluated two such regression-based controllers, along with conventional, sequential two-site control with co-contraction mode switching (SeqCon), in box-block, refined-clothespin and door-knob tasks, on 10 able-bodied and 4 limb-absent subjects. Subjects operated a commercial hand and wrist using a socket bypass harness. One 2-DoF controller (DirCon) related the intuitive hand actions of open-close and pronation-supination to the associated prosthesis hand-wrist actions, respectively. The other (MapCon) mapped myoelectrically more distinct, but less intuitive, actions of wrist flexion-extension and ulnar-radial deviation. Each 2-DoF controller was calibrated from separate 90 s calibration contractions. SeqCon performed better statistically than MapCon in the predominantly 1-DoF box-block task (>20 blocks/minute vs. 8-18 blocks/minute, on average). In this task, SeqCon likely benefited from an ability to easily focus on 1-DoF and not inadvertently trigger co-contraction for mode switching. The remaining two tasks require 2-DoFs, and both 2-DoF controllers each performed better (factor of 2-4) than SeqCon. We also compared the use of 12 vs. 6 optimally-selected EMG electrodes as inputs, finding no statistical difference. Overall, we provide further evidence of the benefits of regression-based EMG prosthesis control of 2-DoFs in the hand-wrist.
最近的研究提出了两种基于表面肌电信号的二自由度(DoF)、同步、独立和比例控制手腕假肢的方法,这些信号来自残余肌肉作为控制输入。我们评估了两种基于回归的控制器,以及传统的、顺序的、带有协同收缩模式切换的双位点控制(SeqCon),在盒子块、精细夹钳和门把手任务中,对 10 名健全人和 4 名肢体缺失的受试者进行了测试。受试者使用插座旁路线束操作商业手和手腕。一种 2-DoF 控制器(DirCon)将直观的手动作,如张开-闭合和旋前-旋后,分别与相关的假肢手-腕动作联系起来。另一种(MapCon)映射出更具区别性但不那么直观的腕关节屈伸和尺桡偏动作。每个 2-DoF 控制器都是从单独的 90 秒校准收缩中校准的。在主要为 1-DoF 的盒子块任务中,SeqCon 在统计学上的表现优于 MapCon(>20 个/分钟,平均为 8-18 个/分钟)。在这个任务中,SeqCon 可能受益于能够轻松专注于 1-DoF 而不会无意中触发协同收缩以进行模式切换。剩下的两个任务需要 2-DoF,两种 2-DoF 控制器的表现都优于 SeqCon(2-4 倍)。我们还比较了使用 12 个与 6 个最佳选择的肌电电极作为输入,发现没有统计学差异。总体而言,我们进一步证明了回归基肌电假肢控制在手-腕 2-DoF 中的优势。