Existing robotic lower-limb prostheses use autonomous control to address cyclic, locomotive tasks, but they are inadequate to operate the prosthesis for daily activities that are non-cyclic and unpredictable. To address this challenge, this study aims to design a novel electromyography (EMG)-driven musculoskeletal model for volitional control of a robotic ankle-foot prosthesis. This controller places the user in continuous control of the device, allowing them to freely manipulate the prosthesis behavior at will. The Hill-type muscle model was used to model a dorsiflexor and a plantarflexor, which functioned around a virtual ankle joint. The model parameters were determined by fitting the model prediction to the experimental data collected from an able-bodied subject. EMG signals recorded from ankle agonist and antagonist muscle pair were used to activate the virtual muscle models. This model was validated via offline simulations and real-time prosthesis control. Additionally, the feasibility of the proposed prosthesis control on assisting the user's functional tasks was demonstrated. The present control may further improve the function of robotic prosthesis for supporting versatile activities in individuals with lower-limb amputations.
翻译:现有机器人低lim假肢使用自主控制处理循环、运动机能任务,但不足以为非周期和无法预测的日常活动操作假肢。为了应对这一挑战,本研究旨在设计一种新型电磁学(EMG)驱动的肌肉骨骼模型,用于自动控制机器人脚踝脚底假肢。该控制器将用户置于该设备的连续控制之下,允许他们自由操作自觉的假肢行为。Hill型肌肉模型被用于模拟多立体动力器和计划动力器,该模型在虚拟脚踝联合体周围运行。模型参数的确定是通过将模型预测与从一个健全身体主体收集的实验数据相匹配而确定的。从脚踝手脚步和对立肌肉对立的EMG信号被用于激活虚拟肌肉模型。该模型通过离线模拟和实时假肢控制得到验证。此外,在协助用户支持功能任务的拟议假肢控制方面,在虚拟脚踝联合体系上运行的模型的可行性也得到了证明。当前控制系统可进一步改进了个人在多功能方面支持。