Johnson Thomas
Department of Computer Science, Nottingham Trent University, United Kingdom.
Data Brief. 2025 Mar 4;59:111442. doi: 10.1016/j.dib.2025.111442. eCollection 2025 Apr.
Urban environments play a critical role in shaping mental wellbeing, yet their impact remains understudied, particularly in relation to environmental air quality and human physiology. Despite this growing awareness of the importance of mental health in urban planning, challenges in integrating diverse datasets, spanning environmental, physiological, and self-reported mental wellbeing data limit the scope of research in this area. The DigitalExposome dataset addresses this gap by providing a comprehensive resource for understanding the relationship between these factors. The resulting data was collected from October 2021 to September 2022 in Nottingham, UK with the dataset including over 42, 437 samples from 40 participants aged between 18-50. Participants conducted a walk through diverse urban environments including polluted and green spaces, while carrying a custom-built environmental monitoring system (Enviro-IoT), wearing an Empatica E4 wearable, and using a smartphone mobile application to self-label mental wellbeing via emojis. Environmental variables (e.g., a range of particulates and gases including particulate matter and nitrogen dioxide), physiological metrics (e.g., HR, HRV, EDA, BVP), and mental wellbeing labels were recorded. Data was processed following collection through resampling and interpolation, and normalization for analysis. This novel dataset lays the groundwork for exploring the relationships between air quality, physiological changes, and mental wellbeing, offering valuable insights for urban planning and public health
城市环境在塑造心理健康方面起着关键作用，但其影响仍未得到充分研究，特别是在环境空气质量与人体生理机能的关系方面。尽管人们越来越意识到心理健康在城市规划中的重要性，但整合环境、生理和自我报告的心理健康数据等多种数据集面临的挑战限制了该领域的研究范围。DigitalExposome数据集通过提供一个全面的资源来理解这些因素之间的关系，填补了这一空白。所得数据于2021年10月至2022年9月在英国诺丁汉收集，该数据集包含来自40名年龄在18至50岁之间参与者的超过42437个样本。参与者在包括污染区域和绿地在内的不同城市环境中行走，同时携带一个定制的环境监测系统（环境物联网），佩戴Empatica E4可穿戴设备，并使用智能手机移动应用程序通过表情符号对心理健康进行自我标注。记录环境变量（例如，一系列颗粒物和气体，包括颗粒物和二氧化氮）、生理指标（例如，心率、心率变异性、皮肤电活动、血压）和心理健康标签。数据在收集后通过重采样、插值和归一化处理进行分析。这个新颖的数据集为探索空气质量、生理变化和心理健康之间的关系奠定了基础，为城市规划和公共卫生提供了有价值的见解。
