Smartphone Mobility Data : A novel proof-of-concept study conducted by University of Maryland researchers has demonstrated that high-fidelity mobility data collected from iPhones can reliably predict recovery outcomes following lower-extremity fractures. This innovative approach could transform how clinicians assess and counsel patients during post-injury rehabilitation. The findings were recently published in the Journal of Bone & Joint Surgery.
Background
Regaining mobility is a top priority for patients recovering from lower-extremity fractures. Historically, clinicians have had limited tools to measure functional recovery. However, iPhones equipped with advanced sensors now offer continuous, real-world mobility tracking, providing a rich dataset of pre- and post-injury gait metrics.
Study Overview
Researchers enrolled 107 adult patients (mean age: 45 years; 43% female; 62% White, 36% Black, 1% Asian, 1% multiracial) who were at least six months post-surgical treatment for a lower-extremity fracture. Participants consented to share Apple iPhone mobility data, including step count, walking speed, step length, walking asymmetry, and double-support time.
These mobility metrics were integrated with demographic and injury data. Using nonlinear modeling, the team evaluated whether pre-injury mobility could predict post-fracture recovery.
Key Findings
Pre-injury mobility was a strong predictor of post-injury function across all models.
Model performance ranged from an adjusted R² of 0.18 (walking asymmetry) to 0.61 (double-support time).
On average, patients increased their daily step count by 65 steps per week post-injury (95% CI: 56–75).
The most significant gains occurred within the first six weeks (92 steps/week; 95% CI: 58–127), compared to 20–26 weeks post-injury (19 steps/week; 95% CI: 11–27; p < 0.001).
Each additional 1,000 pre-injury steps correlated with 301 more daily steps post-injury (95% CI: 235–367).
Walking speed declined by 0.200 m/s in the first eight weeks post-injury but improved by 0.071 m/s between weeks 12 and 26.
Conclusion
These proof-of-concept findings underscore the value of smartphone-derived mobility data in forecasting recovery trajectories. Personalized recovery projections could enhance patient counseling and provide actionable insights for orthopedic surgeons.
"The study reflects University of Maryland's commitment to clinical innovation and interdisciplinary collaboration at the intersection of medicine and technology. We’re now expanding this work across additional subspecialities of orthopaedics, including sports medicine, joint replacement, shoulder surgery, and foot and ankle care." Nathan O'Hara, PhD, MHA, Associate Professor of Orthopaedics, University of Maryland School of Medicine.
“This novel approach has the potential to reshape how orthopaedic care is delivered—empowering patients with clearer expectations, enabling earlier detection of complications, and supporting more personalized, data-driven recovery plans. We also have an app under development to support this work, with plans to launch multicenter trials later this year.” Brian Shear, MD, Orthopaedic Surgery Resident, University of Maryland Medical Center. Newswise/SP