Retrospective Analysis of Movement Data Before and After an Ankle Fracture: A Descriptive Study Using Apple Health
Journal article, 2026

Objective: To evaluate movement patterns in patients with ankle fractures before and after injury. Patients and Methods: This descriptive study analyzed movement data from patients treated for ankle fractures at Sahlgrenska University Hospital, Sweden (January 1 to December 31, 2022). Patients were identified using ICD-10 codes and medical records. Inclusion criteria: surgical and nonsurgically treated patients with >6 months of preinjury iPhone use. Step count, length, and speed were collected through a mobile application integrated with Apple Health. Double support and gait asymmetry were excluded due to limited external validity. Data spanned 6-12 months preinjury to 1 year post-injury. The primary aim was to evaluate whether patients reach their preinjury movement patterns. Results: Of 1131 patients, 90 were analyzed. Preinjury means: 5435.0 steps (SD 4215.3), step length 0.70 m (SD 0.07), and step speed 1.28 m/s (SD 0.2). At 1 year: 5420.3 steps (SD 3887.0), step length 0.68 m (SD 0.08), and step speed 1.22 m/s (SD 0.19). A post-injury plateau was reached in step parameters at 84.8 days, with no further recovery thereafter. Step count largely recovered, but deficits in step length and speed persisted at 12 months. Conclusion: Smartphone-derived movement data provide a cost-effective alternative to laboratory gait analysis, enabling long-term monitoring. Preinjury data allow individualized baseline comparisons and may support earlier identification of patients needing adjusted rehabilitation.

Author

Erik Börjesson

Sahlgrenska University Hospital

University of Gothenburg

Emilia Möller Rydberg

University of Gothenburg

Sahlgrenska University Hospital

Carl Bergdahl

Sahlgrenska University Hospital

University of Gothenburg

Sebastian Andreasson

University of Gothenburg

Torbjörn Lundh

Okinawa Institute of Science and Technology Graduate University

University of Gothenburg

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Michael Möller

University of Gothenburg

Sahlgrenska University Hospital

David Wennergren

Sahlgrenska University Hospital

University of Gothenburg

Mayo Clinic Proceedings Digital Health

29497612 (eISSN)

Vol. 4 2 100362

Subject Categories (SSIF 2025)

Sport and Fitness Sciences

DOI

10.1016/j.mcpdig.2026.100362

More information

Latest update

5/29/2026