| Title | HRV4Training: Large-scale longitudinal training load analysis in unconstrained free-living settings using a smartphone application. | ||
| Author | Altini, Marco; Amft, Oliver | ||
| Journal | Annu Int Conf IEEE Eng Med Biol Soc | Publication Year/Month | 2016-Aug |
| PMID | 28268857 | PMCID | -N/A- |
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.