Mobile psychiatry: towards improving the care for bipolar disorder

Pawel Prociow*, Katarzyna Wac, John Crowe

*Corresponding author for this work
    15 Citations (Scopus)

    Abstract

    Background: Mental health has long been a neglected problem in global healthcare. The social and economic impacts of conditions affecting the mind are still underestimated. However, in recent years it is becoming more apparent that mental disorders are a growing global concern and there is a necessity of developing novel services and researching effective means of providing interventions to sufferers. Such novel services could include technology-based solutions already used in other healthcare applications but are yet to make their way into standard psychiatric practice.Methods: This manuscript proposes a system where sensors are utilised to devise an " early warning" system for patients with bipolar disorder. The system, containing wearable and environmental sensors, would collect behavioural data independent from the patient's self-report. To test the feasibility of the concept, a prototype system was devised, which was followed by trials including four healthy volunteers as well as a bipolar patient.Results: The sensors utilised in the study yielded behavioural data which may be of significant use in detecting early effects of a bipolar episode. Basic processing performed on particular data inputs provided information about activity patterns in areas, which are usually strongly influenced by the course of Bipolar Disorder.Conclusions: The manuscript discusses the basic usage issues and other barriers which are to be tackled before technology-based approaches to mental care can be successfully rolled out and their true value appraised.

    Original languageEnglish
    Article number5
    JournalInternational Journal of Mental Health Systems
    Volume6
    ISSN1752-4458
    DOIs
    Publication statusPublished - 29 May 2012

    Keywords

    • Bipolar disorder
    • Mental health
    • Personalized monitoring
    • Pervasive monitoring

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