ADARP: A Multi Modal Dataset for Stress and Alcohol Relapse Quantification in Real Life Setting
ADARP: A Multi Modal Dataset for Stress and Alcohol Relapse Quantification in Real Life Setting
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ADARP：现实生活环境中压力和酒精复吸量化的多模态数据集
DOI：
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发表时间：
2022
期刊：
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通讯作者：
M. Cleveland
中科院分区：
文献类型：
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作者：
Ramesh Kumar Sah;M. McDonell;Patricia Pendry;Sara Parent;Hassan Ghasemzadeh;M. Cleveland
基于可穿戴传感器数据的压力检测和分类是一个新兴的研究领域，对个人的身心健康具有重要意义。在这项工作中，我们引入了一个新的数据集，ADARP，它包含了在真实世界的门诊环境中收集的生理数据和自我报告结果，涉及被诊断为酒精使用障碍的个体。我们描述了用户研究，提供了数据集的细节，建立了生理数据和自我报告结果之间的显著相关性，展示了压力分类，并将我们的数据集公开以促进研究。
Stress detection and classification from wearable sensor data is an emerging area of research with significant implications for individuals’ physical and mental health. In this work, we introduce a new dataset, ADARP, which contains physiological data and self-report outcomes collected in real-world ambulatory settings involving individuals diagnosed with alcohol use disorders. We describe the user study, present details of the dataset, establish the significant correlation between physiological data and self-reported outcomes, demonstrate stress classification, and make our dataset public to facilitate research.