Fan, D., Yang, X., Zhao, N., Guan, L. and Abbasi, Q. H. (2022) Exercise monitoring and assessment system for home-based respiratory rehabilitation. IEEE Sensors Journal, 22(19), pp. 18890-18902. (doi: 10.1109/JSEN.2022.3200984)
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Abstract
Exercise training is a key component of respiratory rehabilitation. Exercise monitoring and assessment have shown to be beneficial and have significant improvement in the outcome of exercise training. In this paper, we propose a non-invasive exercise monitoring and assessment system (EMAS) to home-based respiratory rehabilitation exercises. EMAS exploits multi-band microwave sensing technique to monitor in real-time the patient’s rehabilitation exercise training, and synchronously provide an online visual feedback for helping the patient better training. Then EMAS extracts exercise information (duration, intensity and breathing changes) from all exercise data to assess the quality of rehabilitation exercise. We implement EMAS on the designed compact and portable prototypes and deploy it to monitor 4 subjects, resulting in one week of exercise data in total. System evaluations demonstrate that EMAS can accurately monitor rehabilitation exercises of each subject and obtain the exercise duration, exercise intensity and breathing changes during rehabilitation exercises to achieve exercise assessment.
Item Type: | Articles |
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Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Abbasi, Professor Qammer |
Authors: | Fan, D., Yang, X., Zhao, N., Guan, L., and Abbasi, Q. H. |
College/School: | College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering |
Journal Name: | IEEE Sensors Journal |
Publisher: | IEEE |
ISSN: | 1530-437X |
ISSN (Online): | 1558-1748 |
Published Online: | 29 August 2022 |
Copyright Holders: | Copyright © 2022 IEEE |
First Published: | First published in IEEE Sensors Journal 22(19): 18890-188902 |
Publisher Policy: | Reproduced in accordance with the publisher copyright policy |
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