步态训练机器人Lokomat在机器人康复期间进行临床评估

L. Lünenburger, G. Colombo, R. Riener, V. Dietz
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引用次数: 81

摘要

神经系统疾病,如脊髓损伤、中风和创伤性脑损伤,会影响患者的运动表现。最重要的结果是功能丧失,例如步态功能。正常特征的减少和病理特征的增加导致这种损失。肌无力和增加的不随意肌张力(痉挛)是最常见的影响。机器人康复设备可用于重新训练受损的功能。例如,Lokomat在体重支撑的跑步机训练中为患者提供支持。机器人设备配备了传感器(例如位置和力)和控制所需的执行器。除了纯粹的训练,先进的工具可以使用这些传感器和执行器来测量使用该设备的患者的生理和其他特性。我们在此报告Lokomat工具的设计、实施和首次测试,这些工具允许(i)测量痉挛和(ii)测量随意肌力。痉挛工具测量控制被动腿部运动时的机械刚度。自愿力工具测量髋关节和膝关节的最大等距扭矩。痉挛程度越高,机械僵硬度越高。自主力工具可用于不完全性脊髓损伤患者。我们的结论是,在训练期间使用机器人设备对患者进行评估将是未来机器人支持治疗的有效和重要补充。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Clinical assessments performed during robotic rehabilitation by the gait training robot Lokomat
Neurological disorders, such as spinal cord injury, stroke, and traumatic brain injury, affect the motor performance of affected individuals. The most important result is the loss of function, e.g. gait function. A reduction of normal features and an increase in pathological features lead to this loss. Muscle weakness and increased involuntary muscle tone (spasticity) are most commonly affected. Robotic rehabilitation devices are available for re-training impaired functions. For example, the Lokomat supports patients during body-weight supported treadmill training. The robotic devices are equipped with sensors (e.g. position and force) and actuators needed for their control. Beyond pure training, advanced tools can use these sensors and actuators to measure physiological and other properties of the patient using the device. We report here the design, implementation, and first tests of tools that allow (i) measurement of spasticity and (ii) measurement of voluntary muscle force with the Lokomat. The spasticity tool measures mechanical stiffness during controlled passive movements of the legs. The voluntary force tool measures maximum isometric torque in the hip and knee joint. Mechanical stiffness is higher in patients with higher spasticity. The voluntary force tool can be used in patients with incomplete spinal cord injury. We conclude that the use of robotic devices for assessment of patients during their training would be an efficient and important addition to robotic-supported therapy in the future.
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