A Comparative Analysis of Android and iOS Mobile Applications for Heart Rate and Walk Tracking

Abstract

Background: The rapid expansion of mobile health (mHealth) applications has revolutionized cardiovascular health and physical activity monitoring, yet limited comparative evidence exists regarding the accuracy, usability, and privacy of heart rate and walk-tracking apps across Android and iOS platforms. Objective: This study aimed to systematically compare the leading Android and iOS mobile applications for heart rate and walk tracking, focusing on data accuracy, usability, privacy features, and user satisfaction, to inform evidence-based app selection in clinical and personal health contexts. Methods: A cross-sectional observational design was used, conducted at Liaquat University of Medical & Health Sciences from January to April 2025. Commercially available apps with ≥1 million downloads, a ≥4.0 user rating, English language availability, and major updates within the prior year were included; apps restricted to research use or requiring proprietary hardware were excluded. Each eligible app underwent duplicate, blinded testing on Android and iOS devices, benchmarking heart rate and step count accuracy against validated reference devices. Usability and privacy were assessed via standardized expert reviews and privacy policy analysis. Descriptive and inferential statistics, including t tests, Mann–Whitney U, and regression, were performed in SPSS v28; IRB approval was obtained in accordance with the Helsinki Declaration. Results: Apple Health demonstrated superior heart rate accuracy (mean difference 1.2 bpm, 95% CI: 0.6–1.8), privacy (mean 4.9/5), and usability (mean 4.6/5), significantly outperforming Google Fit and Samsung Health (p < 0.001), while apps with native wearable integration achieved greater measurement precision and higher user satisfaction (odds ratio 5.8, 95% CI: 1.2–27.5, p = 0.021). Conclusion: iOS-based apps, particularly Apple Health, provide more accurate, user-friendly, and privacy-conscious heart rate and walk tracking, supporting their preferential selection for patient self-management and clinical monitoring.