Research Article
Can You Form Healthy Habit? Predicting Habit Forming States through Mobile Phone
@INPROCEEDINGS{10.4108/icst.bodynets.2013.253658, author={bin xu and Yin Bai and Haifeng Yang and Jian Cui and Shuyang Jiang}, title={Can You Form Healthy Habit? Predicting Habit Forming States through Mobile Phone}, proceedings={8th International Conference on Body Area Networks}, publisher={ICST}, proceedings_a={BODYNETS}, year={2013}, month={10}, keywords={mobile phone sensor mobile healthcare mobile social network factor graph healthy habit}, doi={10.4108/icst.bodynets.2013.253658} }- bin xu
Yin Bai
Haifeng Yang
Jian Cui
Shuyang Jiang
Year: 2013
Can You Form Healthy Habit? Predicting Habit Forming States through Mobile Phone
BODYNETS
ACM
DOI: 10.4108/icst.bodynets.2013.253658
Abstract
Health-compromising behaviors are difficult to change since people do not behave in accordance with their intention. This paper aims at studying the extent to which a person's healthy habit forming process can be affected by mobile phone usage. We propose a novel healthy habit forming states predicting framework using mobile phone platform. First we present a definition for the healthy habit forming process consisting of several states. We define the social intervention types and user context data which are extracted from mobile phone sensor data. Then we make use of machine learning methods to study the correlation between these data and healthy habit forming states. Specifically, a predicting model called Habits Factor Graph(HaFG) is proposed to predict the habit forming states. To evaluate our work, an Android based prototype system is implemented. Experimental results show that the healthy habit forming states are predicted possibly from user context information with a fairly good accuracy (around 67%).