Our long term goal is to push further our knowledge on complex relations between physiological data, lifestyle and performance by providing consumers with a clinical grade tool, and outsourcing data collection to thousand of users, effectively carrying out a massive research study. In this section we will be including peer reviewed publications and other posts covering our approach and findings. You can also find all our publications at this page on Research Gate.
2017. D.J. Plews, B. Scott, M. Altini, M. Wood, A.E. Kilding and P.B. Laursen, "Comparison of heart rate variability recording with smart phone photoplethysmographic, Polar H7 chest strap and electrocardiogram methods", accepted for publication in the International Journal of Sports Physiology and Performance. Full text here.
2017. M. Altini, C. Van Hoof, O. Amft, "Relation Between Estimated Cardiorespiratory Fitness and Running Performance in Free-Living: an Analysis of HRV4Training Data ", accepted for publication at BHI 2017. Full paper at this link.
2016. M. Altini, O. Amft, "HRV4Training: Large-Scale Longitudinal Training Load Analysis in Unconstrained Free-Living Settings Using a Smartphone Application", accepted for publication at EMBC 2016. Full paper.
2017. S. Williams, T. Booton, M. Watson, D. Rowland, M. Altini, "Heart Rate Variability is a Moderating Factor in the Workload-Injury Relationship of Competitive CrossFit™ Athletes" Journal of Sports Science and Medicine. Full text here.
2016. M. Altini, P. Casale, J. Penders, O. Amft, "Cardiorespiratory fitness estimation in free-living using wearable sensors" accepted for publication in Artificial Intelligence in Medicine. Full paper.
2016. M. Altini, P. Casale, J. Penders, O. Amft, "Cardiorespiratory fitness estimation using wearable sensors: laboratory and free-living analysis of context-specific submaximal heart rates". Accepted for publication in the Journal of Applied Physiology. Full paper.
From the Quantified Self to Epidemiological Research covers the first three years of HRV4Training and the approach described above, in more details. Full story here. Training (mostly) slow to race (kind of) fast is about training polarization, the data analyzed in this post inspired some of the latest HRV4Training features.