Beyond Mobile Apps: a Survey of Technologies for Mental Well-being

Kieran Woodward, Eiman Kanjo, David J Brown, T.Martin McGinnity, Becky Inster, Donald J Macintyre, Athanasios Tsanas

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Abstract

Mental health problems are on the rise globally and strain national health systems worldwide. Mental disorders are closely associated with fear of stigma, structural barriers such as financial burden, and lack of available services and resources which often prohibit the delivery of frequent clinical advice and monitoring. Technologies for mental well-being exhibit a range of attractive properties, which facilitate the delivery of state-of-the-art clinical monitoring. This review article provides an overview of traditional techniques followed by their technological alternatives, sensing devices, behaviour changing tools, and feedback interfaces. The challenges presented by these technologies are then discussed with data collection, privacy, and battery life being some of the key issues which need to be carefully considered for the successful deployment of mental health toolkits.
Finally, the opportunities this growing research area presents are discussed including the use of portable tangible interfaces combining sensing and feedback technologies. Capitalising on the data these ubiquitous devices can record, state of the art machine learning algorithms can lead to the development of robust clinical decision support tools towards diagnosis and improvement of mental well-being delivery in real-time.
Original languageEnglish
Article number1949-3045
JournalIEEE Transactions on Affective Computing
Early online date7 Aug 2020
DOIs
Publication statusE-pub ahead of print - 7 Aug 2020

Keywords

  • Pervasive computing ,
  • Mental Well-being
  • Machine learning ,
  • Ubiquitous computing
  • Physiological Measures ,

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