Anicai Cezar, Shakir Muhammad Zeeshan
University of the West of Scotland, School of Computing, Engineering and Physical Sciences, Paisley, PA1 2BE, United Kingdom.
Sci Data. 2025 May 22;12(1):844. doi: 10.1038/s41597-025-05051-3.
In a rapidly evolving technological landscape across various industries, the emergence of real-time, context-aware solutions for health monitoring holds great promise. The dataset presented here encompasses signals from two domains. Ambient environment signals and physiological responses are captured to provide context for well-being assessment. Cardiac activity and electrodermal activity were selected as health indicators, while indoor ambient conditions were characterized by parameters such as temperature, humidity, light, sound, pressure and air quality as determined by Volatile Organic Compounds (VOCs) and Particulate Matter (PM). Data collection involved 14 participants, with each participant contributing approximately 48 minutes of data. This process resulted in a total of over 600 minutes of data, recorded under varied indoor ambient conditions. This dataset was utilized for classifying ambient environment risks concerning long-term cardiac health and for estimating physiological responses exclusively from ambient environment parameters. The compiled dataset provides opportunities for examining the connections between indoor climates and individuals' well-being states in diverse environments, thereby enabling additional investigations and applications in the domain of context-aware technology.
在各个行业快速发展的技术格局中，用于健康监测的实时、情境感知解决方案的出现前景广阔。此处呈现的数据集包含来自两个领域的信号。采集环境信号和生理反应以提供健康评估的背景信息。心脏活动和皮肤电活动被选作健康指标，而室内环境条件则由温度、湿度、光照、声音、压力以及由挥发性有机化合物（VOCs）和颗粒物（PM）测定的空气质量等参数来表征。数据收集涉及14名参与者，每位参与者贡献约48分钟的数据。这一过程总共产生了超过600分钟的数据，这些数据是在不同的室内环境条件下记录的。该数据集用于对与长期心脏健康相关的环境风险进行分类，并仅根据环境参数估计生理反应。汇编的数据集为研究不同环境中室内气候与个人健康状态之间的联系提供了机会，从而能够在情境感知技术领域进行更多的研究和应用。
