Research Article
Conceptualization of a Personalized eCoach for Wellness Promotion
@INPROCEEDINGS{10.1145/3154862.3154930, author={Martin Gerdes and Santiago Martinez and Dian Tjondronegoro}, title={Conceptualization of a Personalized eCoach for Wellness Promotion}, proceedings={11th EAI International Conference on Pervasive Computing Technologies for Healthcare}, publisher={ACM}, proceedings_a={PERVASIVEHEALTH}, year={2018}, month={1}, keywords={ecoach holistic observation personalized recommendations reinforcement hci personalization machine learning big data ai}, doi={10.1145/3154862.3154930} }- Martin Gerdes
Santiago Martinez
Dian Tjondronegoro
Year: 2018
Conceptualization of a Personalized eCoach for Wellness Promotion
PERVASIVEHEALTH
ACM
DOI: 10.1145/3154862.3154930
Abstract
Evidence-based health promotion programs implement clinical practice guidelines built upon results of clinical trials with a definite number of participants, collected during a specific period of time. Wearable technologies allow for continuous observation of wellness parameters of multiple citizens, combined with monitoring of activities and context parameters involved in citizens’ wellness. A statistical inference model can describe the relation between multidimensional activities and context parameters, the wellness of an individual and a comparable reference group, utilizing machine learning techniques and knowledge from continuous observations of multiple citizens.
This paper presents a holistic concept of a coach system, namely eCoach, that combines specialized medical evidence available from randomized control trials, with individual and reference knowledge to create and reinforce wellness-based recommendations. The eCoach adapts these recommendations in a continuous personalized coaching dialog addressing citizen’s needs and preferences.
