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Stretch with Stretch: Physical Therapy Exercise Games Led by a Mobile Manipulator

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arxiv 2312.13279 v2 pith:4ABSGA2O submitted 2023-12-20 cs.RO

classification cs.RO
keywords exercisephysicalstretchrobotsystemusersadherenceestimated
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Physical therapy (PT) is a key component of many rehabilitation regimens, such as treatments for Parkinson's disease (PD). However, there are shortages of physical therapists and adherence to self-guided PT is low. Robots have the potential to support physical therapists and increase adherence to self-guided PT, but prior robotic systems have been large and immobile, which can be a barrier to use in homes and clinics. We present Stretch with Stretch (SWS), a novel robotic system for leading stretching exercise games for older adults with PD. SWS consists of a compact and lightweight mobile manipulator (Hello Robot Stretch RE1) that visually and verbally guides users through PT exercises. The robot's soft end effector serves as a target that users repetitively reach towards and press with a hand, foot, or knee. For each exercise, target locations are customized for the individual via a visually estimated kinematic model, a haptically estimated range of motion, and the person's exercise performance. The system includes sound effects and verbal feedback from the robot to keep users engaged throughout a session and augment physical exercise with cognitive exercise. We conducted a user study for which people with PD (n=10) performed 6 exercises with the system. Participants perceived the SWS to be useful and easy to use. They also reported mild to moderate perceived exertion (RPE).

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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Exercise Specialists Evaluation of Robot-led Physical Therapy for People with Parkinsons Disease

    cs.RO 2025-02 conditional novelty 4.0 of 10

    A user study with 11 exercise specialists finds broadly positive reception of a robot-led physical therapy system for Parkinson's disease, with calls for more human-like feedback and easier use.

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