Abstract
Physical activity (PA) is a major contributor for both physical and mental wellbeing, and it is also needed to maintain our working capability. PA is not only about sports and exercise, but also being active at work, home, in commuting and during leisure time. According to WHO physical inactivity accounts globally for more than 3 million deaths annually. Evidence-based interventions to under-stand and increase our PA behaviour are therefore important. Activity monitors provide a means to set targets for daily activity and to follow the intensity, frequency, and duration of PA. Monitoring dai-ly activity has been shown to motivate for PA but more information is needed to understand our daily PA behaviour. Our daily PA is correlated to our daily habits such as steps and calories burned and sleeping time. The current randomized control trail study try to understand by visualising and cluster-ing daily PA (>3.5 MET), steps, calories and sleep of the baseline and the week 8 in working days, from Monday to Friday. The data analysis is based on self-organizing maps (SOMs) technique. The data clusters reveal changes and differences the intervention has occurred between men and women in their PA behaviour.
Recommended Citation
Koskivaara, Eija, "ANALYSING PHYSICAL ACTIVITY BEHAVIOUR WITH SELF-ORGANIZING MAPS – A RCT STUDY WITH POLAR ACTIVE" (2016). PACIS 2016 Proceedings. 22.
https://aisel.aisnet.org/pacis2016/22