Erol Duygun, Sarkar Nilanjan
Department of Electrical and Electronics Engineering, Yeditepe University, Kayisdagi, Istanbul, 34755, Turkey.
IEEE Trans Neural Syst Rehabil Eng. 2008 Jun;16(3):278-85. doi: 10.1109/TNSRE.2008.922668.
Recent research in rehabilitation indicates that tasks that focus on activities of daily living (ADL) are likely to show significant increase in motor recovery after stroke. Most ADL tasks require patients to coordinate their arm and hand movements to complete these tasks. This paper presents a new control approach for robot-assisted rehabilitation of stroke patients that enables them to perform ADL by providing controlled and coordinated assistance to both arm and hand movement. The control architecture is represented in terms of a hybrid system model combining a high-level controller for decision-making and two low-level assistive controllers (arm and hand controllers) for arm and hand motion assistance. The presented controller is implemented on a test-bed and the results of this implementation are presented to demonstrate the feasibility of the proposed control architecture.
近期康复研究表明,专注于日常生活活动(ADL)的任务在中风后运动恢复方面可能会有显著改善。大多数ADL任务要求患者协调手臂和手部动作来完成这些任务。本文提出了一种用于中风患者机器人辅助康复的新控制方法,通过为手臂和手部动作提供受控且协调的辅助,使患者能够执行ADL。控制架构以混合系统模型表示,该模型结合了用于决策的高级控制器和用于手臂及手部运动辅助的两个低级辅助控制器(手臂和手部控制器)。所提出的控制器在试验台上实现,并展示了该实现结果以证明所提控制架构的可行性。