Research Article
A Smartphone-Based Personalized Activity Recommender System for Patients with Depression
@ARTICLE{10.4108/eai.14-10-2015.2261655, author={Galen Chin-Lun Hung and Pei-Ching Yang and Chen-Yi Wang and Jung-Hsien Chiang}, title={A Smartphone-Based Personalized Activity Recommender System for Patients with Depression}, journal={EAI Endorsed Transactions on Cognitive Communications}, volume={2}, number={9}, publisher={ACM}, journal_a={COGCOM}, year={2015}, month={12}, keywords={depression, metal health, smartphone, usage patterns, emotion, context-aware, recommender}, doi={10.4108/eai.14-10-2015.2261655} }- Galen Chin-Lun Hung
Pei-Ching Yang
Chen-Yi Wang
Jung-Hsien Chiang
Year: 2015
A Smartphone-Based Personalized Activity Recommender System for Patients with Depression
COGCOM
EAI
DOI: 10.4108/eai.14-10-2015.2261655
Abstract
Depression is a common mental illness worldwide. Apart of pharmacological treatment and psychotherapy, self-management of negative emotions is of paramount importance, because relapse of depression often results from an inadequate response to negative emotions. The purpose of this study is to design and implement a personal recommender system, for emotion regulation. It assists users to be aware of negative emotions and guides them to deal with it with behavioral activation. It analyzes the smartphone usage patterns to predict the emergence of negative emotions, while integrating data obtained from context awareness and psychiatrists' recommendations to suggest relevant emotion-regulating activities. In this pilot study, we recruited 15 normal subjects to use our recommender application for 14 days. Our system has successfully recommended activities matched to subjects' intent, and their negative emotions attenuated substantially after engaging in the activities. The presented system has a potential to provide personalized and pervasive mental health services for patients with depression.
Copyright © 2015 G. C.-L. Hung et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
