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Digital Phenotyping of Mental Health using multimodal sensing of multiple situations of interest: A Systematic Literature Review by Ivan Moura; Ariel Teles; Davi Viana; Jean Marques; Luciano Coutinho; Francisco Silva is a Computer Science article available to read on EtoBox.

What is Digital Phenotyping of Mental Health using multimodal sensing of multiple situations of interest: A Systematic Literature Review about?

Many studies have used Digital Phenotyping of Mental Health (DPMH) to complement classic methods of mental health assessment and monitoring. This research area proposes innovative methods that perform multimodal sensing of multiple situations of interest (e.g., sleep, physical activity, mobility) to health professionals. In this paper, we present a Systematic Literature Review (SLR) to recognize, characterize and analyze the state of the art on DPMH using multimodal sensing of multiple situations of interest to professionals. We searched for studies in six digital libraries, which resulted in 1865 retrieved published papers. Next, we performed a systematic process of selecting studies based on inclusion and exclusion criteria, which selected 59 studies for the data extraction phase. First, based on the analysis of the extracted data, we describe an overview of this field, then presenting characteristics of the selected studies, the main mental health topics targeted, the physical and virtual sensors used, and the identified situations of interest. Next, we outline answers to research questions, describing the context data sources used to detect situations, the DPMH workflow used fo

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Author

Ivan Moura; Ariel Teles; Davi Viana; Jean Marques; Luciano Coutinho; Francisco Silva

Publisher

Elsevier BV

Published

2023

Language

EN

Field

Computer Science (Physical Sciences)