Joint Department of Biomedical Engineering, North Carolina State University, Raleigh, NC 27695, USA.
Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Sci Robot. 2023 Oct 25;8(83):eadf5758. doi: 10.1126/scirobotics.adf5758. Epub 2023 Oct 18.
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.
目前的下肢假肢在姿势控制任务中不能提供主动辅助来维持使用者的平衡,尤其是在受到干扰的情况下。在这项研究中,我们旨在通过实现对机器人下肢假肢的神经控制来解决这个缺失的功能。具体来说,使用从拮抗的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)直接且连续地驱动机器人假肢踝关节。招募了接受胫骨截肢的参与者,并对他们进行了使用 EMG 驱动的机器人踝关节的训练。我们研究了与使用日常被动设备相比,使用 EMG 控制的踝关节如何影响参与者在预期干扰下的预期和补偿性姿势控制策略和稳定性。我们研究了参与者在姿势摆动任务中使用任一设备时的神经肌肉协调(通过分析运动模块)与健全对照者的相似性。结果表明,与他们的被动假肢相比,EMG 控制的假肢使参与者能够使用近乎正常的姿势控制策略,这表现在完整假肢的压力中心和关节角度的对称性得到了改善。参与者的姿势稳定性得到了显著提高,这表现在使用 EMG 控制的假肢踝关节时,跌倒或摔倒的次数减少了。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向未截肢个体的结构靠拢。在这里,我们已经证明了直接 EMG 控制机器人下肢假肢的潜在益处,以恢复正常的姿势控制策略(神经和生物力学),从而提高截肢者使用者的站立姿势稳定性。