Wearable-Enhanced mHealth Intervention to Promote Physical Activity in Manual Wheelchair Users: Single-Group Pre-Post Feasibility Study

Zijian Huang; Dan McCoy; Rosemarie Cooper; Theresa M Crytzer; Yueyang Chi; Dan Ding

doi:10.2196/70063

Wearable-Enhanced mHealth Intervention to Promote Physical Activity in Manual Wheelchair Users: Single-Group Pre-Post Feasibility Study

JMIR Rehabil Assist Technol. 2025 Jun 5:12:e70063. doi: 10.2196/70063.

Authors

Zijian Huang¹, Dan McCoy², Rosemarie Cooper², Theresa M Crytzer³, Yueyang Chi^{1

4}, Dan Ding¹

Affiliations

¹ Department of Rehabilitation Science and Technology, School of Health and Rehabilitation Sciences, University of Pittsburgh, 6425 Penn Ave, Suite 401, Pittsburgh, PA, 15206, United States, 1 4126241964.
² Department of Veteran Affairs Pittsburgh Healthcare System, Human Engineering Research Laboratories, Pittsburgh, PA, United States.
³ Department of Physical Therapy, John G Rangos Sr School of Health Sciences, Duquesne University, Pittsburgh, PA, United States.
⁴ Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States.

PMID: 40472238
PMCID: PMC12161616
DOI: 10.2196/70063

Abstract

Background: With the rapid advancement of technology, using wearable devices and mobile health (mHealth) apps to monitor and promote physical activity (PA) has become increasingly popular among individuals with various chronic conditions. However, such work remains limited among individuals with spinal cord injury (SCI), especially those who use a manual wheelchair for mobility.

objectives: The study aims to describe the development of the WheelFit mHealth app for monitoring and promoting PA in manual wheelchair users (MWUs) with SCI and evaluate its feasibility and usability in free-living conditions.

Methods: The WheelFit app, based on the Fogg Behavioral Model with inputs from stakeholders, including MWUs, physical therapists, and personal trainers, was developed to promote PA in MWUs. It works with two commercial wearable devices, that is, an Android smartwatch and a wheel sensor, which stream users' upper extremity and wheelchair movement to the app to calculate PA variables using custom algorithms. Users can set personal goals, review daily progress and PA history, and access an adaptive workout library within the app. A 4-week single-group pre-post study, consisting of a 1-week baseline and 3-week intervention phase, was conducted to evaluate WheelFit's feasibility and usability. Feasibility was evaluated using the session attendance rate, device and app usage, and implementation of action plans. Usability was assessed using the system usability scale. The preliminary effectiveness was assessed by comparing preintervention and postintervention PA variables and scores from the SCI exercise self-efficacy scale.

Results: A total of 16 participants completed the study protocol with 100% session attendance and maintained 14.2 hours of daily device and app connection. Participants demonstrated varying levels of adherence to their action plans. The excellent usability of WheelFit was indicated by an average system usability scale score of 81.8 (SD 19.2) points. Statistically significant increases between pre-post daily exercise times (preintervention: mean 26.4, SD 16.9 minutes; postintervention: mean 33.3, SD 24.9 minutes; P=.049) and exercise self-efficacy scale scores (preintervention: mean 33.9, SD 4.5 points; postintervention: mean 35.9, SD 3.2 points; P=.043) were observed.

Conclusions: The WheelFit app demonstrated promising feasibility, usability, and a positive impact on promoting PA in MWUs with SCI. Future investigation exploring the potential integration of the WheelFit app into clinical practice is warranted.

Keywords: community-based research; exercise; mHealth; spinal cord injury; telemedicine; telerehabilitation; workout.