Research Article
Will You Have a Good Sleep Tonight? Sleep Quality Prediction with Mobile Phone
@INPROCEEDINGS{10.4108/icst.bodynets.2012.250091, author={yin bai and Bin Xu and Yuanchao Ma and Guodong Sun and Yu Zhao}, title={Will You Have a Good Sleep Tonight? Sleep Quality Prediction with Mobile Phone}, proceedings={7th International Conference on Body Area Networks}, publisher={ICST}, proceedings_a={BODYNETS}, year={2012}, month={11}, keywords={mobile phone sensing sleep quality prediction factor graph model android system}, doi={10.4108/icst.bodynets.2012.250091} }- yin bai
Bin Xu
Yuanchao Ma
Guodong Sun
Yu Zhao
Year: 2012
Will You Have a Good Sleep Tonight? Sleep Quality Prediction with Mobile Phone
BODYNETS
ICST
DOI: 10.4108/icst.bodynets.2012.250091
Abstract
In this paper, we propose a novel sleep quality predicting framework from user context information extracted from mobile phone data. A combination of the machine learning technology and medical knowledge is used to study the relation between context and sleep quality, so that sleep quality can be predicted in real time. We develop a prototype system called SleepMiner, which uses mobile phone data such as mobile sensor data and communication data to extract human context information. Then the relationship between context data and sleep quality is analyzed and a learning model based on factor graph model is proposed to predict sleep quality. Experimental result shows that it is possible to accurately infer sleep quality (around 78%) from user context information. A set of solutions are proposed to make the SleepMiner system setup suitable for daily usage with minimal impact on the phone's resources. Experiments are also carried out to evaluate our design in effectiveness and efficiency.
