IoT-Based Preventive Mental Health Using Knowledge Graphs and Standards for Better Well-Being
| dc.contributor.author | Gyrard, Amelie | |
| dc.contributor.author | Mohammadi, Ali | |
| dc.contributor.author | Gaur, Manas | |
| dc.contributor.author | Kung, Antonio | |
| dc.date.accessioned | 2025-11-21T00:29:43Z | |
| dc.date.issued | 2025-12-15 | |
| dc.description.abstract | Sustainable Development Goals (SDGs) give the UN a road map for development with Agenda 2030 as a target. SDG3 "Good Health and Well-Being" ensures healthy lives and promotes well-being for all ages. Digital technologies can support SDG3. Burnout and even depression could be reduced by encouraging better preventive health. Due to the lack of patient knowledge and focus to take care of their health, it is necessary to help patients before it is too late. New trends such as positive psychology and mindfulness are highly encouraged in the USA. Digital Twins (DTs) can help with the continuous monitoring of emotion using physiological signals (e.g., collected via wearables). DTs facilitate monitoring and provide constant health insight to improve quality of life and well-being with better personalization. Healthcare DTs challenges are standardizing data formats, communication protocols, and data exchange mechanisms. As an example, ISO has Internet of Things (IoT) and DTs Working Group. To achieve those data integration and knowledge challenges, we designed the Mental Health Knowledge Graph (KG) (ontology and dataset) to boost mental health; which acquires knowledge from ontology-based mental health projects classified within the LOV4IoT ontology catalog (Emotion, Depression, and Mental Health). Furthermore, the KG is mapped to standards from ETSI SmartM2M such as SAREF for eHealth Ageing Well domain to represent medical devices and sensors. | |
| dc.description.sponsorship | We want to acknowledge the Kno.e.sis research team (lead by Professor Amit Sheth) from Wright State University, Ohio, USA for fruitful discussions about related topics such as "Mental Health/Depression/Suicide", and "Semantic, Cognitive, and Perceptual Computing" and with cognitive psychologists such as Professor Valerie Shalin during Dr. Gyrard’s post-doc in 2018-2019. This work has partially received funding from the European Union’s Horizon 2020 research and innovation program under project grant agreement StandICT.eu 2026 No. 101091933 (open call). We would like to thank the project partners for their valuable comments. The opinions expressed are those of the authors and do not reflect those of the sponsors. | |
| dc.description.uri | https://www.taylorfrancis.com/chapters/edit/10.1201/9781003630685-8/iot-based-preventive-mental-health-using-knowledge-graphs-standards-better-well-being-amelie-gyrard-seyedali-mohammadi-manas-gaur-antonio-kung | |
| dc.format.extent | 21 pages | |
| dc.genre | book chapters | |
| dc.genre | postprints | |
| dc.identifier | doi:10.13016/m2mvwy-nh4m | |
| dc.identifier.citation | Gyrard, Amelie, Seyedali Mohammadi, Manas Gaur, and Antonio Kung. “IoT-Based Preventive Mental Health Using Knowledge Graphs and Standards for Better Well-Being.” In Smart Technologies for Sustainable Development Goals. CRC Press, 2025. https://doi.org/10.1201/9781003630685-8 | |
| dc.identifier.uri | https://doi.org/10.1201/9781003630685-8 | |
| dc.identifier.uri | http://hdl.handle.net/11603/40787 | |
| dc.language.iso | en | |
| dc.publisher | Taylor & Francis | |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Student Collection | |
| dc.relation.ispartof | UMBC Computer Science and Electrical Engineering Department | |
| dc.relation.ispartof | UMBC Faculty Collection | |
| dc.rights | It is deposited under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License https://creativecommons.org/licenses/by-nc-nd/4.0/deed.en which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/deed.en | |
| dc.subject | Well-Being | |
| dc.subject | Mental Health | |
| dc.subject | Health Ontology | |
| dc.subject | UMBC Ebiquity Research Group | |
| dc.subject | Semantic Web Technologies | |
| dc.subject | Standard | |
| dc.title | IoT-Based Preventive Mental Health Using Knowledge Graphs and Standards for Better Well-Being | |
| dc.type | Text | |
| dcterms.creator | https://orcid.org/0000-0002-5411-2230 |
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