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.

中文翻译：

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下肢触觉康复机器人的设计和验证。


目前用于研究下肢运动控制和康复的机器人侧重于步态训练。另一种方法是专注于恢复前驱能力，例如运动适应和意志运动，这在上肢机器人治疗中很常见。在这里，我们描述了 NOTTABIKE，这是一款单自由度康复机器人，旨在探索和提升这些潜在能力。卧式健身车平台由伺服电机提供动力，并配有角度编码器、力扭矩感应踏板和无线肌电图系统。从弹簧质量阻尼器系统到新颖的脚到曲柄机械定律的虚拟环境呈现了腿部伸展和踩踏板任务的变体，这些任务挑战了感知、认知、运动规划和电机控制系统。本文描述了 NOTTABIKE 的动态性能和触觉渲染准确性，并提供了一个示例电机适应任务来说明其使用。扭矩和速度模式控制器显示出接近统一的幅值比，并且在高达 10 Hz 时相位损失小于 60 度。弹簧渲染的刚度平均误差为 1%，阻尼器渲染的平均误差为 2.5%。虚拟质量渲染不太准确，但在不同的感知质量方面取得了成功。 NOTTABIKE 将用于研究完好者和受损者的下肢运动适应，并制定促进意志运动恢复的康复方案。