Wearable Devices and AI Techniques Integration to Promote Physical Activity

被引：5

作者：

Baretta, Dario ^{[1
]}

Sartori, Fabio ^{[2
]}

Greco, Andrea ^{[1
]}

Melen, Riccardo ^{[2
]}

Stella, Fabio ^{[2
]}

Bollini, Letizia ^{[1
]}

D'addario, Marco ^{[1
]}

Steca, Patrizia ^{[1
]}

机构：

[1] Univ Milano Bicocca, Dept Psychol, Milan, Italy

[2] Univ Milano Bicocca, Dept Informat Syst & Commun, Milan, Italy

来源：

PROCEEDINGS OF THE 18TH INTERNATIONAL CONFERENCE ON HUMAN-COMPUTER INTERACTION WITH MOBILE DEVICES AND SERVICES (MOBILEHCI 2016) | 2016年

关键词：

Bayesian Networks; Expert Systems; Wearable Devices; Self-Efficacy; Behavior Change Techniques;

D O I：

10.1145/2957265.2965011

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：1105 / 1108

页数：4

共 11 条

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