amsys 13(01-06): e2

Research Article

Managing Data in Help4Mood

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  • @ARTICLE{10.4108/trans.amsys.01-06.2013.e2,
        author={Maria K. Wolters and Juan Mart\^{\i}nez-Miranda and Soraya Estevez and Helen F. Hastie and Colin Matheson},
        title={Managing Data in Help4Mood},
        journal={EAI Endorsed Transactions on Ambient Systems},
        keywords={XML, depression, SNOMED CT, decision support},
  • Maria K. Wolters
    Juan Martínez-Miranda
    Soraya Estevez
    Helen F. Hastie
    Colin Matheson
    Year: 2013
    Managing Data in Help4Mood
    DOI: 10.4108/trans.amsys.01-06.2013.e2
Maria K. Wolters1, Juan Martínez-Miranda2, Soraya Estevez3, Helen F. Hastie4, Colin Matheson1
  • 1: School of Informatics, 10 Crichton Street, Edinburgh EH8 9aB, University of Edinburgh Edinburgh, UK
  • 2: IBIME, Universitat Politécnica de Valencia, Valencia, Spain
  • 3: Fundaciò i2CAT, Barcelona, Spain
  • 4: School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh, UK


Help4Mood is a system that supports the treatment of people with depression in the community. It collects rich cognitive, psychomotor, and motor data through a Personal Monitoring System and a Virtual Agent, which is then analysed by a Decision Support System; analysis results are fed back to patients and their treating clinicians. In this paper, we describe how the complex data is managed and discuss ethical issues. Data is stored in functional units that correspond to treatment relevant entities. Custom XML DTDs are defined for each unit, which are used to exchange information between system components. As far as possible, observations and findings are coded using SNOMED CT to ensure interoperability with other applications such as Electronic Health Records.