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SleepSight: A wearables-based relapse prevention system for Schizophrenia

Kerz, M; Folarin, A; Meyer, N; Begale, M; MacCabe, J; Dobson, RJ; (2016) SleepSight: A wearables-based relapse prevention system for Schizophrenia. In: Lukowicz, P and Krüger, A and Bulling, A and Lim, YK and Patel, SN, (eds.) UbiComp '16: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct. (pp. pp. 113-116). Association for Computing Machinery (ACM): New York, NY, USA. Green open access

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Abstract

SleepSight is a novel approach to detecting early signs of relapse in psychosis, thereby allowing targeted intervention for relapse prevention. The system uses a wireless-enabled wearable device and smartphone to collect longitudinal accelerometry, heart-rate, ambient light and smartphone usage patterns from patients living in their homes. These data are encrypted and sent via the mobile data network to a secure server for real-Time analysis, using the Purple Robot mobile application. This study tested feasibility and acceptability of the SleepSight system in 15 participants with a diagnosis of schizophrenia. Patient recruitment and data collection was completed in January 2016, at the South London and Maudsley NHS Foundation Trust (SLaM), the largest mental health service provider in the EU. The project is a unique multidisciplinary collaboration between the NIHR Biomedical Research Centre for Mental Health, the Institute of Psychiatry, Psychology and Neuroscience, and the National Health Service.

Type: Proceedings paper
Title: SleepSight: A wearables-based relapse prevention system for Schizophrenia
Event: UbiComp '16 Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct (UbiComp '16)
ISBN-13: 9781450344623
Open access status: An open access version is available from UCL Discovery
DOI: 10.1145/2968219.2971419
Publisher version: http://dx.doi.org/10.1145/2968219.2971419
Language: English
Additional information: Copyright is held by the owner/author(s).
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Pop Health Sciences > Institute of Health Informatics
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Pop Health Sciences > Institute of Health Informatics > Clinical Epidemiology
URI: http://discovery.ucl.ac.uk/id/eprint/1528435
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