Musculoskeletal conditions, often requiring rehabilitation, affect one-third of the U.S. population annually. This paper presents rehabilitation assistive technology that includes body-worn motion sensors and a mobile application that extends the reach of a physical rehabilitation specialist beyond the clinic to ensure that home exercises are performed with the same precision as under clinical supervision. Assisted by a specialist in the clinic, the wearable sensors and user interface developed allow the capture of individualized exercises unique to the patient’s physical abilities. Beyond the clinical setting, the system can assist patients by providing real-time corrective feedback to repeat these exercises through a correct and complete arc of motion for the prescribed number of repetitions. An inertial measurement unit (IMU) is used on the body part to be exercised to capture its pose. In this paper, we present a kinematics data processing approach to defining custom exercises with flexibility in terms of where it is worn and the nature of the exercise, as well as real-time corrective feedback parameters. The system is tested on two exercises performed by a healthy individual to demonstrate the feasibility and accuracy of the approach. We demonstrate how it can improve exercise adherence by assisting users in reaching the full prescribed range of motion and stay on the ideal plane of motion and improve hold time. Preliminary results from an ongoing clinical trial are presented.

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Published in IEEE Access, v. 10.

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/

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This work was supported by the National Science Foundation under Award 1722619 and Award 1722652.