Project News

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.

 We are glad to invite you to the AGEING@WORK hybrid workshop ‘ “Aging and Workability: Engaging older workers in the era of digitalization” that will be organized on Wednesday, May 25th, from 9-11 CET, hosted by the ARIDOS VI Congreso National OVIEDO 2022 at Oviedo, Spain, and broadcasted online at the same time.


Pervasive technologies such as Artifcial Intelligence, Virtual Reality and the Internet of Things, despite their great potential for improved workability and well-being of older workers, entail wide ethical concerns, with opaque ethical boundaries that can not be covered by existing legislation


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