Current lower-limb prostheses do not provide active assistance in postural control tasks to maintain the user’s balance, particularly in situations of perturbation. In this study, we aimed to address this missing function by enabling neural control of robotic lower-limb prostheses. Specifically, electromyographic (EMG) signals (amplified neural control signals) recorded from antagonistic residual ankle muscles were used to drive a robotic prosthetic ankle directly and continuously. Participants with transtibial amputation were recruited and trained in using the EMG-driven robotic ankle. We studied how using the EMG-controlled ankle affected the participants’ anticipatory and compensatory postural control strategies and stability under expected perturbations compared with using their daily passive devices. We investigated the similarity of neuromuscular coordination (by analyzing motor modules) of the participants, using either device in a postural sway task, to that of able-bodied controls. Results showed that, compared with their passive prosthesis, the EMG-controlled prosthesis enabled participants to use near-normative postural control strategies, as evidenced by improved between-limb symmetry in intact-prosthetic center-of-pressure and joint angle excursions. Participants substantially improved postural stability, as evidenced by a reduction in steps or falls using the EMG-controlled prosthetic ankle. Furthermore, after relearning to use residual ankle muscles to drive the robotic ankle in postural control, nearly all participants’ motor module structure shifted toward that observed in individuals without limb amputations. Here, we have demonstrated the potential benefit of direct EMG control of robotic lower limb prostheses to restore normative postural control strategies (both neural and biomechanical) toward enhancing standing postural stability in amputee users.

中文翻译：

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神经假体控制可恢复站立姿势控制中接近正常的神经力学

目前的下肢假肢无法在姿势控制任务中提供主动帮助以维持用户的平衡，特别是在扰动的情况下。在这项研究中，我们的目标是通过对机器人下肢假肢进行神经控制来解决这一缺失的功能。具体来说，从对抗性残余踝关节肌肉记录的肌电图（EMG）信号（放大的神经控制信号）被用来直接连续地驱动机器人假肢踝关节。招募了经过胫骨截肢的参与者，并接受了使用肌电图驱动的机器人脚踝的培训。我们研究了与使用日常被动设备相比，使用肌电图控制的脚踝如何影响参与者的预期和补偿性姿势控制策略以及预期扰动下的稳定性。我们研究了在姿势摇摆任务中使用任一设备的参与者的神经肌肉协调（通过分析运动模块）与健全对照的相似性。结果表明，与被动假肢相比，肌电图控制的假肢使参与者能够使用接近标准的姿势控制策略，完整假肢压力中心和关节角度偏移的肢体间对称性得到改善就证明了这一点。参与者的姿势稳定性得到了显着改善，使用肌电图控制的假肢踝关节减少了步数或跌倒就证明了这一点。此外，在重新学习使用残余踝关节肌肉来驱动机器人踝关节进行姿势控制后，几乎所有参与者的运动模块结构都转向了在没有截肢的个体中观察到的结构。在这里，我们证明了直接肌电图控制机器人下肢假肢的潜在好处，可以恢复规范的姿势控制策略（神经和生物力学），从而增强截肢者的站立姿势稳定性。