A Cyber-Physical System for Near Real-Time Monitoring of At-Home Orthopedic Rehabilitation and Mobile-Based Provider-Patient Communications to Improve Adherence: Development and Formative Evaluation

Timothy Stevens; Ryan S McGinnis; Blake Hewgill; Rebecca H Choquette; Timothy W Tourville; Jean Harvey; Richard Lachapelle; Bruce D Beynnon; Michael J Toth; Christian Skalka

doi:10.2196/16605

A Cyber-Physical System for Near Real-Time Monitoring of At-Home Orthopedic Rehabilitation and Mobile-Based Provider-Patient Communications to Improve Adherence: Development and Formative Evaluation

JMIR Hum Factors. 2020 May 11;7(2):e16605. doi: 10.2196/16605.

Authors

Affiliations

¹ Department of Computer Science, University of Vermont, Burlington, VT, United States.
² Department of Electrical and Biomedical Engineering, University of Vermont, Burlington, VT, United States.
³ Department of Orthopedics and Rehabilitation, University of Vermont, Burlington, VT, United States.
⁴ Department of Rehabilitation and Movement Sciences, University of Vermont, Burlington, VT, United States.
⁵ Department of Nutrition and Food Sciences, University of Vermont, Burlington, VT, United States.
⁶ Department of Molecular Physiology and Biophysics, University of Vermont, Burlington, VT, United States.
⁷ Department of Medicine, University of Vermont, Burlington, VT, United States.

PMID: 32384052
PMCID: PMC7248795
DOI: 10.2196/16605

Abstract

Background: Knee extensor muscle performance is reduced after lower extremity trauma and orthopedic surgical interventions. At-home use of neuromuscular electrical stimulation (NMES) may improve functional recovery, but adherence to at-home interventions is low. Greater benefits from NMES may be realized with closer monitoring of adherence to at-home prescriptions and more frequent patient-provider interactions.

Objective: This study aimed to develop a cyber-physical system to monitor at-home adherence to NMES prescription and facilitate patient-provider communications to improve adherence in near real time.

Methods: The RehabTracker cyber-physical system was developed to accomplish this goal and comprises four components: (1) hardware modifications to a commercially available NMES therapy device to monitor device use and provide Bluetooth functionality; (2) an iPhone Operating System-based mobile health (mHealth) app that enables patient-provider communications in near real time; (3) a clinician portal to allow oversight of patient adherence with device use; and (4) a back-end server to store data, enable adherence analysis, and send automated push notifications to the patient. These four elements were designed to be fully compliant with the Health Insurance Portability and Accountability Act. The system underwent formative testing in a cohort of patients following anterior cruciate ligament rupture (n=7) to begin to assess face validity.

Results: Compared with the NMES device software-tracked device use, the RehabTracker system recorded 83% (40/48) of the rehabilitation sessions, with 100% (32/32) of all sessions logged by the system in 4 out of 7 patients. In patients for whom tracking of automated push notifications was enabled, 100% (29/29) of the push notifications sent by the back-end server were received by the patient. Process, hardware, and software issues contributing to these inaccuracies are detailed.

Conclusions: RehabTracker represents a promising mHealth app for tracking and improving adherence with at-home NMES rehabilitation programs and warrants further refinement and testing.

Keywords: device use tracking; digital health; exercise; internet of things; mHealth; mobile health; neuromuscular electrical stimulation; rehabilitation; smart devices.

©Timothy Stevens, Ryan S McGinnis, Blake Hewgill, Rebecca H Choquette, Timothy W Tourville, Jean Harvey, Richard Lachapelle, Bruce D Beynnon, Michael J Toth, Christian Skalka. Originally published in JMIR Human Factors (http://humanfactors.jmir.org), 11.05.2020.

Grants and funding

R21 CA191532/CA/NCI NIH HHS/United States