Web: http://arxiv.org/abs/2205.03116

May 9, 2022, 1:11 a.m. | Dimitris Spathis, Ignacio Perez-Pozuelo, Tomas I. Gonzales, Soren Brage, Nicholas Wareham, Cecilia Mascolo

cs.LG updates on arXiv.org arxiv.org

Cardiorespiratory fitness is an established predictor of metabolic disease
and mortality. Fitness is directly measured as maximal oxygen consumption
(VO2max), or indirectly assessed using heart rate response to a standard
exercise test. However, such testing is costly and burdensome, limiting its
utility and scalability. Fitness can also be approximated using resting heart
rate and self-reported exercise habits but with lower accuracy. Modern
wearables capture dynamic heart rate data which, in combination with machine
learning models, could improve fitness prediction.

In …

arxiv fitness free prediction sensors wearable wearable sensors

More from arxiv.org / cs.LG updates on arXiv.org

Director, Applied Mathematics & Computational Research Division

@ Lawrence Berkeley National Lab | Berkeley, Ca

Business Data Analyst

@ MainStreet Family Care | Birmingham, AL

Assistant/Associate Professor of the Practice in Business Analytics

@ Georgetown University McDonough School of Business | Washington DC

Senior Data Science Writer

@ NannyML | Remote

Director of AI/ML Engineering

@ Armis Industries | Remote (US only), St. Louis, California

Digital Analytics Manager

@ Patagonia | Ventura, California