Towards Machine Learning on Data from Professional Cyclists

Ivarsson, Oscar,1988Chalmers tekniska högskola,Chalmers University of Technology (författare)

Professional sports are developing towards increasingly scientific training methods with increasing amounts of data being collected from laboratory tests, training sessions and competitions. In cycling, it is standard to equip bicycles with small computers recording data from sensors such as power-meters, in addition to heart-rate, speed, altitude etc. Recently, machine learning techniques have provided huge success in a wide variety of areas where large amounts of data (“big data”) is available. In this paper, we perform a pilot experiment on machine learning to model physical response in elite cyclists. As a first experiment, we show that it is possible to train a LSTM machine learning algorithm to predict the heart-rate response of a cyclist during a training session. This work is a promising first step towards developing more elaborate models based on big data and machine learning to capture performance aspects of athletes.

Hilmkil, Agrin,1991Chalmers tekniska högskola,Chalmers University of Technology(Swepub:cth)agrin (författare)
Johansson, Moa,1981Chalmers tekniska högskola,Chalmers University of Technology(Swepub:cth)jomoa (författare)
Kuylenstierna, Dan,1976Chalmers tekniska högskola,Chalmers University of Technology(Swepub:cth)danku (författare)
Van Erp, TeunVrije Universiteit Amsterdam (VU) (författare)
Chalmers tekniska högskolaVrije Universiteit Amsterdam (VU) (creator_code:org_t)

Ingår i:Proceedings of the XII World Congress of Performance Analysis of Sport2018

Av författaren/redakt...: Ivarsson, Oscar, ...; Hilmkil, Agrin, ...; Johansson, Moa, ...; Kuylenstierna, D ...; Van Erp, Teun

Om ämnet

MEDICIN OCH HÄLSOVETENSKAP: MEDICIN OCH HÄLS ...; och Hälsovetenskap; och Idrottsvetenskap

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.