Worker behaviour & affective traits monitoring methods & infrastructure

A report on worker behavior and affective traits monitoring methods and infrastructure at the Ageing @ Work platform.

d4.2_worker_behaviour_affective_traits.pdf

Project News

Jun

06

2022

By contentuser

The prediction of sedentary behaviour in Ageing@Work system

Sedentary behavior is considered as a major public health challenge, linked with many chronic diseases and premature mortality. In Ageing@Work, we developed a machine learning approach to integrate prediction of sedentary behavior within our Virtual Coach, using daily step counts as input. Machine learning algorithms are using as input the daily steps of the last seven days in order to predict the possibility of sedentary behavior for the upcoming day.

May

30

2022

By contentuser

Ageing @ Work final project meeting

9th and final Consortium meeting