Sensor-based solutions for mental healthcare: A systematic literature review

TitreSensor-based solutions for mental healthcare: A systematic literature review
Publication TypeConference Paper
Year of Publication2020
AuthorsDrissi, N, Ouhbi, S, García-Berná, JA, Idrissi, MAJ, Ghogho, M
Conference NameHEALTHINF 2020 - 13th International Conference on Health Informatics, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020
Mots-clésBiomedical engineering, Health care, Healthcare delivery, Medical informatics, Mental health, Quality of life, Systematic literature review, Well being
Abstract

Mental well-being is a crucial aspect of the person's general health, compromised mental health impairs the person's functioning, decreases the quality of life, and limits the person's contribution to society. The mental health industry is still facing some barriers to healthcare delivery such as costs, mental health illiteracy, and stigma. Incorporating technological interventions in the treatment and the diagnosis processes might help overcome these barriers. Sensors are devices that have been used for healthcare since the 1990s and have been incorporated into mental healthcare in different forms. In this study, we conducted a systematic literature review to identify and analyze sensor-based solutions for mental healthcare. 12 studies were identified and analyzed. The majority of the selected studies presented methods and models and were empirically evaluated and showed promising accuracy results. Different types of sensors were used to collect different types of data about the patient such as physical and behavioral information. The selected studies mainly addressed the use of sensors for common mental issues like stress and depression or the analysis of general mental status. Some studies reported some limitations mainly related to technological issues and lack of standards. © 2020 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85083705930&partnerID=40&md5=335f69fa969e09929802b364d7f6d696
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