title: HRV4Training: Large-scale longitudinal training load analysis in unconstrained free-living settings using a smartphone application.
abstract: We describe an approach to support athletes at various fitness levels in their training load analysis using heart rate (HR) and heart rate variability (HRV). A smartphone-based application (HRV4Training) was developed that captures heart activity over one to five minutes using photoplethysmography (PPG) and derives HR and HRV features. HRV4Training integrated a guide for an early morning spot measurement protocol and a questionnaire to capture self-reported training activity. The smartphone application was made publicly available for interested users to quantify training effect. Here we analyze data acquired over a period of 3 weeks to 5 months, including 797 users, breaking down results by gender and age group. Our results suggest a strong relation between HR, HRV and self-reported training load independent of gender and age group. HRV changes due to training were larger than those of HR. We conclude that smartphone-based training monitoring is feasible and a can be used as a practical tool to support large populations outside controlled laboratory environments.
authors.forename: Marco
authors.initials: M
authors.lastname: Altini
authors.forename: Oliver
authors.initials: O
authors.lastname: Amft
mesh_terms: D000328:Adult; D056352:Athletes; D003198:Computer Simulation; D005260:Female; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D063731:Mobile Applications; D018670:Monitoring, Ambulatory; D017156:Photoplethysmography / Q000379:methods*; D015203:Reproducibility of Results; D057566:Self Report; D012815:Signal Processing, Computer-Assisted; D000068997:Smartphone; D011795:Surveys and Questionnaires; D013997:Time Factors