A survey of autonomous monitoring systems in mental health
Article
Gopalakrishnan, Abinaya, Gururajan, Raj, Zhou, Xujuan, Venkataraman, Revathi, Chan, Ka Ching and Higgins, Niall. 2024. "A survey of autonomous monitoring systems in mental health." WIREs Data Mining and Knowledge Discovery. 14 (3). https://doi.org/10.1002/widm.1527
Article Title | A survey of autonomous monitoring systems in mental health |
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ERA Journal ID | 201715 |
Article Category | Article |
Authors | Gopalakrishnan, Abinaya, Gururajan, Raj, Zhou, Xujuan, Venkataraman, Revathi, Chan, Ka Ching and Higgins, Niall |
Journal Title | WIREs Data Mining and Knowledge Discovery |
Journal Citation | 14 (3) |
Article Number | e1527 |
Number of Pages | 32 |
Year | 2024 |
Publisher | John Wiley & Sons |
Place of Publication | United Kingdom |
ISSN | 1942-4787 |
1942-4795 | |
Digital Object Identifier (DOI) | https://doi.org/10.1002/widm.1527 |
Web Address (URL) | https://wires.onlinelibrary.wiley.com/doi/10.1002/widm.1527 |
Abstract | Smartphones and personal sensing technologies have made collecting data continuously and in real time feasible. The promise of pervasive sensing technologies in the realm of mental health has recently garnered increased attention. Using Artificial Intelligence methods, it is possible to forecast a person's emotional state based on contextual information such as their current location, movement patterns, and so on. As a result, conditions like anxiety, stress, depression, and others might be tracked automatically and in real-time. The objective of this research was to survey the state-of-the-art autonomous psychological health monitoring (APHM) approaches, including those that make use of sensor data, virtual chatbot communication, and artificial intelligence methods like Machine learning and deep learning algorithms. We discussed the main processing phases of APHM from the sensing layer to the application layer and an observation taxonomy deals with various observation devices, observation duration, and phenomena related to APHM. Our goal in this study includes research works pertaining to working of APHM to predict the various mental disorders and difficulties encountered by researchers working in this sector and potential application for future clinical use highlighted. This article is categorized under: Technologies > Machine Learning Technologies > Prediction Application Areas > Health Care. © 2024 The Authors. WIREs Data Mining and Knowledge Discovery published by Wiley Periodicals LLC. |
Keywords | behavior; monitoring; smartphone sensing; mental health |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 420313. Mental health services |
Byline Affiliations | SRM Institute of Science and Technology, India |
School of Business | |
Royal Brisbane and Women’s Hospital, Australia |
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