Alibeji Naji, Dicianno Brad E, Sharma Nitin
Department of Mechanical Engineering and Materials Science, University of Pittsburgh, Pittsburgh, PA,USA 15261.
Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA,USA 15261.
Int J Intell Robot Appl. 2017 Feb;1(1):6-18. doi: 10.1007/s41315-016-0003-5. Epub 2017 Jan 4.
Currently a telerehabilitation system includes a therapist and a patient where the therapist interacts with the patient, typically via a verbal and visual communication, for assessment and supervision of rehabilitation interventions. This mechanism often fails to provide physical assistance, which is a modus operandi during physical therapy or occupational therapy. Incorporating an actuation modality such as functional electrical stimulation (FES) or a robot at the patient's end that can be controlled by a therapist remotely, to provide therapy or to assess and measure rehabilitation outcomes can significantly transform current telerehabilitation technology. In this paper, a position-synchronization controller is derived for FES-based telerehabilitation to provide physical assistance that can be controlled remotely. The newly derived controller synchronizes an FES-driven human limb with a remote physical therapist's robotic manipulator despite constant bilateral communication delays. The control design overcomes a major stability analysis challenge: the unknown and unstructured nonlinearities in the FES-driven musculoskeletal dynamics. To address this challenge, the nonlinear muscle model was estimated through two neural networks functions that approximated unstructured nonlinearities and an adaptive control law for structured nonlinearities with online update laws. A Lyapunov-based stability analysis was used to prove the globally uniformly ultimately bounded tracking performance. The performance of the state synchronization controller was validated through experiments on an able-bodied subject. Specifically, we demonstrated bilateral control of FES-elicited leg extension and a human operated robotic manipulator. The controller was shown to effectively synchronize the system despite unknown and different delays in the forward and backward channels.
当前,远程康复系统包括治疗师和患者,治疗师通常通过言语和视觉交流与患者互动,以评估和监督康复干预措施。这种机制往往无法提供物理辅助,而物理辅助是物理治疗或职业治疗中的一种操作方式。在患者端加入一种可由治疗师远程控制的驱动方式,如功能性电刺激(FES)或机器人,以提供治疗或评估和测量康复效果,可显著改变当前的远程康复技术。在本文中,为基于FES的远程康复推导了一种位置同步控制器,以提供可远程控制的物理辅助。新推导的控制器能使由FES驱动的人体肢体与远程物理治疗师的机器人操纵器同步,尽管存在持续的双边通信延迟。该控制设计克服了一个主要的稳定性分析挑战:FES驱动的肌肉骨骼动力学中未知且无结构的非线性。为应对这一挑战,通过两个神经网络函数估计非线性肌肉模型,这两个函数分别近似无结构的非线性和具有在线更新律的结构化非线性的自适应控制律。基于李雅普诺夫的稳定性分析被用于证明全局一致最终有界的跟踪性能。通过对一名身体健全的受试者进行实验,验证了状态同步控制器的性能。具体而言,我们展示了对FES诱发的腿部伸展和人工操作的机器人操纵器的双边控制。结果表明,尽管前向和后向通道存在未知且不同的延迟,该控制器仍能有效地使系统同步。