ArticleIEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society2020
Design and Validation of a Lower-Limb Haptic Rehabilitation Robot.
Article in IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review on Haptic Feedback in Medical Robotics: Technologies, Applications, Clinical Translation, and an Information-Oriented Perspective.Sensors (Basel, Switzerland) · 2026Pooled it
- Enhancing lower-limb rehabilitation: a scoping review of augmented reality environment.Journal of neuroengineering and rehabilitation · 2025Article
- Decoding lower-limb kinematic parameters during pedaling tasks using deep learning approaches and EEG.Medical & biological engineering & computing · 2024Article
- Selection of EMG Sensors Based on Motion Coordinated Analysis.Sensors (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.