TY - GEN
T1 - Sensor-based solutions for mental healthcare
T2 - 13th International Conference on Health Informatics, HEALTHINF 2020 - Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020
AU - Drissi, Nidal
AU - Ouhbi, Sofia
AU - Garćia-Berná, José Alberto
AU - Idrissi, Mohammed Abdou Janati
AU - Ghogho, Mounir
N1 - Funding Information:
This paper is part of the Startup project 1093 funded by UAE University (2019-2021).
Publisher Copyright:
© 2020 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - E-mental health
KW - Mental health
KW - Sensors
KW - Systematic literature review
UR - http://www.scopus.com/inward/record.url?scp=85083705930&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85083705930&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85083705930
T3 - HEALTHINF 2020 - 13th International Conference on Health Informatics, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020
SP - 593
EP - 600
BT - HEALTHINF 2020 - 13th International Conference on Health Informatics, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020
A2 - Cabitza, Federico
A2 - Fred, Ana
A2 - Gamboa, Hugo
PB - SciTePress
Y2 - 24 February 2020 through 26 February 2020
ER -