menu ☰
menu ˟

Correlating multimodal physical sensor information with biological analysis in ultra endurance cycling

Creator:

May, Gregory; Doherty, Aiden R.; Smeaton, Alan F.; Warrington, Giles;

Institution: MDPI Publishing
Subject Keywords: Machine learning; Information technology; Performance; Algorithms; Physiology; Sports sciences; ultra-endurance cycling; body sensors; cycling event detection; estimating energy expenditure;
Region:
Description:

The sporting domain has traditionally been used as a testing ground for new technologies which subsequently make their way into the public domain. This includes sensors. In this article a range of physical and biological sensors deployed in a 64 hour ultra-endurance non-stop cycling race are described. A novel algorithm to estimate the energy expenditure while cycling and resting during the event are outlined. Initial analysis in this noisy domain of "sensors in the field" are very encouraging and represent a first with respect to cycling.

Format:

application/pdf

Related: http://doras.dcu.ie/15584/1/SENSORS-03-276-Warrington-ie-final.pdf
Suggested citation:

May, Gregory; Doherty, Aiden R.; Smeaton, Alan F.; Warrington, Giles; . () Correlating multimodal physical sensor information with biological analysis in ultra endurance cycling [Online]. Available from: http://publichealthwell.ie/node/634740 [Accessed: 19th June 2019].

  

View your saved citations and reading lists

Contributor:


 
Click here to view all the resources gathered from this organisation's website.