# IoT-Based Preventive Mental Health Using Knowledge Graphs and Standards for Better Well-Being

**Authors:** Amelie Gyrard, Seyedali Mohammadi, Manas Gaur, Antonio Kung  
**arXiv:** [2406.13791](https://arxiv.org/abs/2406.13791)  
**Date:** 2024-06-19  
**Summary page:** https://www.summarizepaper.com/en/paper/2406.13791v3/

## Key points

- The Sustainable Development Goals (SDGs) set by the UN provide a roadmap for global development, with Agenda 2030 as a target.
- SDG3 focuses on "Good Health and Well-Being" aiming to ensure healthy lives and promote well-being for all age groups.
- Digital technologies play a crucial role in supporting SDG3 initiatives, particularly in addressing issues such as burnout and depression through better preventive healthcare measures.
- Challenges include lack of patient knowledge and motivation to prioritize health until it becomes critical.
- New trends like positive psychology and mindfulness are gaining traction in countries like the USA.
- Use of Digital Twins (DTs) for continuous monitoring of emotions via wearables shows promise in providing personalized insights to improve quality of life.
- Implementing healthcare DTs faces challenges like standardizing data formats, communication protocols, and data exchange mechanisms.
- International standards such as those set by ISO/IEC JTC 1/SC 41 Internet of Things (IoT) and DTs Working Group are crucial to address challenges effectively.
- Efforts are being made to integrate data into a comprehensive Mental Health Knowledge Graph leveraging ontology-based projects related to emotions, depression, and mental health.
- Advancements in Large Language Models (LLMs) show potential in mental health applications but face challenges related to reliability, explainability, trustworthiness assessment.

## Summary

The Sustainable Development Goals (SDGs) set by the UN provide a roadmap for global development, with Agenda 2030 as a target. SDG3 focuses on "Good Health and Well-Being" and aims to ensure healthy lives and promote well-being for all age groups. Digital technologies play a crucial role in supporting SDG3 initiatives, particularly in addressing issues such as burnout and depression through better preventive healthcare measures. However, there is a significant challenge due to the lack of patient knowledge and motivation to prioritize their health until it becomes critical. In response to these challenges, new trends like positive psychology and mindfulness are gaining traction in countries like the USA. Additionally, the use of Digital Twins (DTs) for continuous monitoring of emotions using physiological signals collected via wearables shows promise in providing personalized insights to improve quality of life and overall well-being. However, implementing healthcare DTs comes with its own set of challenges, including standardizing data formats, communication protocols, and data exchange mechanisms. To address these challenges effectively, international standards such as those set by ISO/IEC JTC 1/SC 41 Internet of Things (IoT) and DTs Working Group are crucial. Furthermore, efforts are being made to integrate data from various sources into a comprehensive Mental Health Knowledge Graph that leverages ontology-based projects related to emotions, depression, and mental health. Moreover, advancements in Large Language Models (LLMs) have shown potential in mental health applications but face challenges related to reliability, explainability, trustworthiness assessment. Despite their impressive capabilities in generating human-like responses across various tasks like question-answering and summarization,

LLMs have been criticized for providing inaccurate information or hallucinations. This poses a significant hurdle in their application within healthcare contexts where consistency and reliability are paramount.