D. Baretta, F. Sartori, A. Greco, R. Melen, Fabio Stella, L. Bollini, M. D'addario, P. Steca
{"title":"Wearable devices and AI techniques integration to promote physical activity","authors":"D. Baretta, F. Sartori, A. Greco, R. Melen, Fabio Stella, L. Bollini, M. D'addario, P. Steca","doi":"10.1145/2957265.2965011","DOIUrl":null,"url":null,"abstract":"Physical activity (PA) is considered one of the most important factors for the prevention and management of non-communicable diseases (NCDs). Mobile technologies offer several opportunities for supporting PA, especially if combined with psychological aspects, model-based reasoning systems and personalized human computer interaction. This still on-going research aims at developing a scalable framework that targets PA promotion among both clinical and non-clinical population, exploiting Bayesian Networks and Expert Systems to characterize and predict qualitative variables like self-efficacy. The expected outcomes are the collection and management of real-time behavioral and psychological data to define a personalized strategy for increasing PA.","PeriodicalId":131157,"journal":{"name":"Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct","volume":"80 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2957265.2965011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
Physical activity (PA) is considered one of the most important factors for the prevention and management of non-communicable diseases (NCDs). Mobile technologies offer several opportunities for supporting PA, especially if combined with psychological aspects, model-based reasoning systems and personalized human computer interaction. This still on-going research aims at developing a scalable framework that targets PA promotion among both clinical and non-clinical population, exploiting Bayesian Networks and Expert Systems to characterize and predict qualitative variables like self-efficacy. The expected outcomes are the collection and management of real-time behavioral and psychological data to define a personalized strategy for increasing PA.