research-article

RehabPhone: a software-defined tool using 3D printing and smartphones for personalized home-based rehabilitation

Authors:

Emery Comstock,

Sutanuka Bhattacharjya,

Lora A Cavuoto,

Wenyao XuAuthors Info & Claims

MobiSys '20: Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services

Pages 434 - 447

https://doi.org/10.1145/3386901.3389028

Published: 15 June 2020 Publication History

Abstract

Approximately 7 million survivors of stroke reside in the United States. Over half of these individuals will have residual deficits, making stroke one of the leading causes of disability. Long-term rehabilitation opportunities are critical for millions of individuals with chronic upper limb motor deicits due to stroke. Traditional in-home rehabilitation is reported to be dull, boring, and un-engaging. Moreover, existing rehabilitation technologies are not user-friendly and cannot be adaptable to different and ever-changing demands from individual stroke survivors. In this work, we present RehabPhone, a highly-usable software-defined stroke rehabilitation paradigm using the smartphone and 3D printing technologies. This software-definition has twofold. First, RehabPhone leverages the cost-effective 3D printing technology to augment ordinal smartphones into customized rehabilitation tools. The size, weight, and shape of rehabilitation tools are software-defined according to individual rehabilitation needs and goals. Second, RehabPhone integrates 13 functional rehabilitation activities co-designed with stroke professionals into a smartphone APP. The software utilizes built-in smartphone sensors to analyzes rehabilitation activities and provides real-time feedback to coach and engage stroke users. We perform the in-lab usability optimization with the RehabPhone prototype with involving 16 healthy adults and 4 stroke survivors. After that, we conduct a 6-week unattended intervention study in 12 homes of stroke residence. In the course of the clinical study, over 32,000 samples of physical rehabilitation activities are collected and evaluated. Results indicate that stroke users with RehabPhone demonstrate a high adherence and clinical efficacy in a self-managed home-based rehabilitation course. To the best of our knowledge, this is the first exploratory clinical study using mobile health technologies in real-world stroke rehabilitation.

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Cited By

Kim DPark JKim MByun SJung CJeong HWoo SLee KLee MJung JLee DRyu BYang SBaek S(2024)Automatic Assessment of Upper Extremity Function and Mobile Application for Self-Administered Stroke RehabilitationIEEE Transactions on Neural Systems and Rehabilitation Engineering10.1109/TNSRE.2024.335849732(652-661)Online publication date: 2024
https://doi.org/10.1109/TNSRE.2024.3358497
Yin YXie LJiang ZXiao FCao JLu S(2024)A Systematic Review of Human Activity Recognition Based on Mobile Devices: Overview, Progress and TrendsIEEE Communications Surveys & Tutorials10.1109/COMST.2024.335759126:2(890-929)Online publication date: Oct-2025
https://doi.org/10.1109/COMST.2024.3357591
Sharma NWaseem MMirzaei SHefeeda MCosta XAl Hassanieh HAsadi ACox LPerino DWidmer JGiustiniano D(2023)MobiSpectral: Hyperspectral Imaging on Mobile DevicesProceedings of the 29th Annual International Conference on Mobile Computing and Networking10.1145/3570361.3613296(1-15)Online publication date: 2-Oct-2023
https://dl.acm.org/doi/10.1145/3570361.3613296
Show More Cited By

Index Terms

RehabPhone: a software-defined tool using 3D printing and smartphones for personalized home-based rehabilitation
1. Human-centered computing
  1. Ubiquitous and mobile computing

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cover image ACM Conferences

MobiSys '20: Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services

June 2020

496 pages

ISBN:9781450379540

DOI:10.1145/3386901

General Chairs:
Eyal de Lara
University of Toronto
,
Iqbal Mohomed
Samsung AI Centre Toronto
,
Program Chairs:
Jason Nieh
Columbia University
,
Elizabeth M. Belding
UC Santa Barbara

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MobiSys '20: The 18th Annual International Conference on Mobile Systems, Applications, and Services

June 15 - 19, 2020

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https://doi.org/10.1109/TNSRE.2024.3358497
Yin YXie LJiang ZXiao FCao JLu S(2024)A Systematic Review of Human Activity Recognition Based on Mobile Devices: Overview, Progress and TrendsIEEE Communications Surveys & Tutorials10.1109/COMST.2024.335759126:2(890-929)Online publication date: Oct-2025
https://doi.org/10.1109/COMST.2024.3357591
Sharma NWaseem MMirzaei SHefeeda MCosta XAl Hassanieh HAsadi ACox LPerino DWidmer JGiustiniano D(2023)MobiSpectral: Hyperspectral Imaging on Mobile DevicesProceedings of the 29th Annual International Conference on Mobile Computing and Networking10.1145/3570361.3613296(1-15)Online publication date: 2-Oct-2023
https://dl.acm.org/doi/10.1145/3570361.3613296
Bsharat BAl-Duhoun AGhanouni P(2023)The acceptance and attitudes towards using assistive technology for people with stroke in Jordan: caregivers’ perspectivesAssistive Technology10.1080/10400435.2023.220272336:1(40-50)Online publication date: 2-May-2023
https://doi.org/10.1080/10400435.2023.2202723
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Sarsenbayeva ZVan Berkel NVelloso EGoncalves JKostakos V(2022)Methodological Standards in Accessibility Research-PLXBCCR- on Motor Impairments: A SurveyACM Computing Surveys10.1145/354350955:7(1-35)Online publication date: 11-Jun-2022
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Bhatia BArinde OTang ZFeng JLawson S(2022)Visualization and Qualitative Analysis of Rehabilitation Exercises Based on a Mobile App2022 IEEE 10th International Conference on Healthcare Informatics (ICHI)10.1109/ICHI54592.2022.00022(67-73)Online publication date: Jun-2022
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Bo WCavuoto LLangan JSubryan HBhattacharjya SHuang MXu W(2022)A progressive prediction model towards home-based stroke rehabilitation programsSmart Health10.1016/j.smhl.2021.10023923(100239)Online publication date: Mar-2022
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Hirasawa YGotoda NKanda RHirata KAkagi R(2020)Promotion System for Home-Based Squat Training Using OpenPose2020 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE)10.1109/TALE48869.2020.9368366(984-986)Online publication date: 8-Dec-2020
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Burns STerblanche MPerea JLillard HDeLaPena CGrinage NMacKinen ACox E(2020)mHealth Intervention Applications for Adults Living With the Effects of Stroke: A Scoping ReviewArchives of Rehabilitation Research and Clinical Translation10.1016/j.arrct.2020.100095(100095)Online publication date: Dec-2020
https://doi.org/10.1016/j.arrct.2020.100095

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