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使用Empatica E4收集的用于压力评估的PPG和EDA数据集。

PPG and EDA dataset collected with Empatica E4 for stress assessment.

作者信息

Campanella Sara, Altaleb Ayham, Belli Alberto, Pierleoni Paola, Palma Lorenzo

机构信息

Department of Information Engineering (DII), Università Politecnica delle Marche, 60131, Ancona, Italy.

出版信息

Data Brief. 2024 Jan 24;53:110102. doi: 10.1016/j.dib.2024.110102. eCollection 2024 Apr.

Abstract

In response to challenging circumstances, the human body can experience marked levels of anxiety and distress. Wearable devices offer a means of real-time and ongoing data collection, facilitating personalized stress monitoring. Therefore, we collected physiological signals (blood pressure volume and electrodermal activities), using Empatica E4, from 29 subjects. A personalized protocol was developed to cause cognitive, mental, and psychological stressors since they are the ones that can be experienced in working or academic environment. We also propose a pipeline to clean and process these two signals to maximize the quality of further analysis. This study aids in the comprehension of the complex connection between stress and working situations by offering a sizable dataset made up of different physiological data. It additionally enables them to create cutting-edge stress-reduction techniques and improving professional achievement while lessening the negative impact of stress on welfare.

摘要

面对具有挑战性的情况时,人体可能会出现明显程度的焦虑和痛苦。可穿戴设备提供了一种实时且持续的数据收集方式,便于进行个性化压力监测。因此,我们使用Empatica E4从29名受试者身上收集了生理信号(血压容积和皮肤电活动)。由于认知、精神和心理压力源是在工作或学术环境中可能遇到的,所以制定了一个个性化方案来引发这些压力源。我们还提出了一个管道来清理和处理这两种信号,以最大限度地提高进一步分析的质量。本研究通过提供一个由不同生理数据组成的大型数据集,有助于理解压力与工作情境之间的复杂联系。此外,它还能使人们创造出前沿的减压技术,提高职业成就,同时减轻压力对幸福感的负面影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41ed/10847510/349d85724a0a/gr1.jpg

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