Face Validity and Usability Evaluation of a Wearable Upper-Limb Motion Sensing System for Home Use
Document Type
Article
Abstract
Comprehensive, real-world data are required to inform the design of more effective rehabilitation strategies and assistive devices for individuals with Parkinson's disease (PD). Parkinsonian tremor, a common symptom affecting the upper limbs, significantly impairs daily activities and quality of life. Traditional clinical assessments of tremor are limited in frequency and scope, often failing to capture the full variability of tremor experienced in daily life. To address this gap, this paper presents a robust, user-friendly wearable upper-limb motion sensing system designed for home use. It incorporates 23 six-axis inertial measurement units to monitor the motion of 21 joints in the hand and upper limb continuously over extended periods. By enabling continuous home-based monitoring, the system can provide valuable insights into the daily impact of tremor and other upper limb pathologies, facilitating personalized treatment plans. The device was tested on seven healthy participants over 48 hours. To complement the quantitative data, participants maintained an activity log and provided qualitative feedback on the device. The results demonstrate that meaningful data can be collected outside a laboratory or clinic. They further inform several recommendations to improve the design of wearable devices for the upper limb. These findings underscore the potential of wearable technology in rehabilitation robotics for long-term monitoring and management of motor symptoms in PD.
Digital Object Identifier (DOI)
Publication Info
Published in IEEE International Conference on Rehabilitation Robotics, 2025, pages 1257-1262.
APA Citation
Kalsi, J., Zhou, Y., Jenkins, M. E., Donelle, L., Trejos, A. L., & Naish, M. D. (2025). Face Validity and Usability Evaluation of a Wearable Upper-Limb Motion Sensing System for Home Use. 2025 International Conference on Rehabilitation Robotics (ICORR), 1257–1262.https://doi.org/10.1109/ICORR66766.2025.11063173
Rights
© 2025, IEEE