IEEE Trans Neural Syst Rehabil Eng. 2020 Jul;28(7):1584-1594. doi: 10.1109/TNSRE.2020.3000735.
Present robots for investigating lower-limb motor control and rehabilitation focus on gait training. An alternative approach is to focus on restoring precursor abilities such as motor adaptation and volitional movement, as is common in upper-limb robotic therapy. Here we describe NOTTABIKE, a one degree-of-freedom rehabilitation robot designed to probe and promote these underlying capabilities. A recumbent exercise cycle platform is powered with a servomotor and instrumented with angular encoders, force-torque sensing pedals, and a wireless EMG system. Virtual environments ranging from spring-mass-damper systems to novel foot-to-crank mechanical laws present variants of leg-reaching and pedaling tasks that challenge perception, cognition, motion planning, and motor control systems. This paper characterizes the dynamic performance and haptic rendering accuracy of NOTTABIKE and presents an example motor adaptation task to illustrate its use. Torque and velocity mode controllers showed near unity magnitude ratio and phase loss less than 60 degrees up to 10 Hz. Spring rendering demonstrated 1% mean error in stiffness, and damper rendering performed comparably at 2.5%. Virtual mass rendering was less accurate but successful in varying perceived mass. NOTTABIKE will be used to study lower-limb motor adaptation in intact and impaired persons and to develop rehabilitation protocols that promote volitional movement recovery.
目前用于研究下肢运动控制和康复的机器人主要集中在步态训练上。另一种方法是专注于恢复运动适应和自主运动等基本能力,这在上肢机器人治疗中很常见。在这里,我们描述了 NOTTABIKE,这是一种单自由度康复机器人,旨在探测和促进这些基本能力。一个卧式运动自行车平台由伺服电机驱动,并配备了角度编码器、力-扭矩感应脚踏板和无线肌电图系统。从弹簧-质量-阻尼系统到新型的脚踏曲柄机械定律的虚拟环境呈现出各种腿部伸展和踩踏任务的变体,这些任务挑战感知、认知、运动规划和运动控制系统。本文描述了 NOTTABIKE 的动态性能和触觉呈现精度,并展示了一个自适应运动任务的示例,以说明其用途。转矩和速度模式控制器在 10 Hz 以下的范围内显示出近单位幅度比和相位损耗小于 60 度。弹簧呈现的刚度平均误差为 1%,阻尼呈现的误差相当,为 2.5%。虚拟质量呈现的精度较低,但成功地改变了感知质量。NOTTABIKE 将用于研究完整和受损个体的下肢运动适应,并开发促进自主运动恢复的康复方案。