Lee Chi-Shiuan, Yu Lo-Ping, Lee Si-Huei, Chen Yi-Chia, Chen Chun-Ta
Department of Mechatronic Engineering, National Taiwan Normal University, 162, Section 1, He-Ping East Rd., Taipei 106, Taiwan.
Attending Physician of Department of Physical Medicine and Rehabilitation, Taipei Veterans General Hospital, 201, Section 2, Shipai Rd., Taipei 106, Taiwan.
Sensors (Basel). 2024 Nov 24;24(23):7498. doi: 10.3390/s24237498.
Parkinson's disease (PD) is a neurodegenerative disorder and always results in balance loss. Although studies in lower-extremity exoskeleton robots are ample, applications with a lower-extremity exoskeleton robot for PD patients are still challenging. This paper aims to develop an effective assistive control for PD patients with a lower-extremity exoskeleton robot to maintain standing balance while being subjected to external disturbances. When an external force is applied to participants to force them to lose balance, the hip strategy for balance recovery based on the zero moment point (ZMP) metrics is used to generate a reference trajectory of the hip joint, and then, a model-free linear extended state observer (LESO)-based fuzzy sliding mode control (FSMC) is synthesized to regulate the human body to recover balance. Balance recovery trials for healthy individuals and PD patients with and without exoskeleton assistance were conducted to evaluate the performance of the proposed exoskeleton robot and balance recovery strategy. Our experiments demonstrated the potential effectiveness of the proposed exoskeleton robot and controller for standing balance recovery control in PD patients.
帕金森病（PD）是一种神经退行性疾病，常导致平衡失调。尽管关于下肢外骨骼机器人的研究很多，但将下肢外骨骼机器人应用于帕金森病患者仍具有挑战性。本文旨在开发一种针对帕金森病患者下肢外骨骼机器人的有效辅助控制方法，以便在受到外部干扰时维持站立平衡。当对参与者施加外力使其失去平衡时，基于零力矩点（ZMP）指标的用于平衡恢复的髋部策略被用于生成髋关节的参考轨迹，然后，合成一种基于无模型线性扩展状态观测器（LESO）的模糊滑模控制（FSMC）来调节人体以恢复平衡。对有和没有外骨骼辅助的健康个体以及帕金森病患者进行了平衡恢复试验，以评估所提出的外骨骼机器人和平衡恢复策略的性能。我们的实验证明了所提出的外骨骼机器人和控制器在帕金森病患者站立平衡恢复控制方面的潜在有效性。
