Review and Content Analysis of Mobile Applications for Heart Rate Variability (Preprint)

<sec> <title>BACKGROUND</title> Heart rate variability (HRV) is increasingly used in health and performance monitoring, though research on its practical applications and the accuracy and validity of these apps remains limited. </sec> <sec> <title>OBJECTIVE</title> This study aims to systematically review and analyse the mobile applications that measure, analyse and provide feedback on HRV. </sec> <sec> <title>METHODS</title> This study was a cross-sectional review of mobile applications for HRV measurement. A systematic search was conducted in the Google Play Store and Apple iTunes Store between October and November 2024. Data were extracted from app descriptions, screenshots, linked websites, and direct communication with developers. </sec> <sec> <title>RESULTS</title> The search yielded 746 smartphone apps, with 231 meeting the eligibility criteria. Most HRV apps originated from the iTunes App Store (74.0%). While 38.3% of app information was publicly available in the app description or website, 46.7% was unobtainable. Most apps (87.0%) reported sensor location, including arm, chest, ear, finger and wrist, and 97.0% reported data storage methods. The majority (67.5%) were free with in-app purchases, and photoplethysmography (PPG) was the most common measurement method (61.5%). For only 71 apps complete data was extractable, of which 61 were unique apps without between-store duplicates. Many of these 61 apps used PPG sensors (39.3%) and time-domain HRV metrics like RMSSD (63.9%) and SDNN (60.7%), with most requiring user-triggered measurements and about 35% supporting continuous monitoring. A majority of apps offered personalized HRV reference scores (65.6%), self-reported stressor tracking (55.7%), and contextual insights or guidance like recovery and readiness scores (73.7%). </sec> <sec> <title>CONCLUSIONS</title> This study highlights the widespread availability but limited transparency and evidence base of heart rate variability apps, underscoring the need for improved data accessibility, measurement validation, and consistency across platforms to enhance their reliability and value for both users and researchers. </sec>