User-centered depression prevention: An EEG approach to pervasive healthcare

Abstract

There have been a number of research projects which have addressed depression, the focus often being on aspects of pharmacology and psychology. Relatively few of the investigations have tried to integrate depression and the related issues into a pervasive depression prevention system incorporating user-centered design. In this paper we propose an approach to provide relief for a user(s) depression by implementing a personalized treatment program; this is implemented in an electroencephalogram (EEG) based music therapy system. EEG plays two roles in this approach: to identify the user (a critical factor in achieving personalized service provision) and to measure the degree of depression. This paper considers the methodology of our EEG approach with design parameters for each component in a pervasive environment. The experiments involved 22 subjects and 4 subjects respectively in user identification and depression detection to evaluate the EEG approach. The results reported are positive and support the conclusion that the EEG approach provides an effective approach to user-centered depression prevention Additionally, the research outcomes support the conclusion that a mobile music therapy system offers beneficial effects for the treatment of depression. The paper concludes with a brief discussion on challenges, outstanding research questions, and future work.