The electrodermal activity (EDA) signal is an electrical manifestation of the sympathetic innervation of the sweat glands. EDA has a history in psychophysiological (including emotional or cognitive stress) research since 1879, but it was not until recent years that researchers began using EDA for pathophysiological applications like the assessment of fatigue, pain, sleepiness, exercise recovery, diagnosis of epilepsy, neuropathies, depression, and so forth. The advent of new devices and applications for EDA has increased the development of novel signal processing techniques, creating a growing pool of measures derived mathematically from the EDA. For many years, simply computing the mean of EDA values over a period was used to assess arousal. Much later, researchers found that EDA contains information not only in the slow changes (tonic component) that the mean value represents, but also in the rapid or phasic changes of the signal. The techniques that have ensued have intended to provide a more sophisticated analysis of EDA, beyond the traditional tonic/phasic decomposition of the signal. With many researchers from the social sciences, engineering, medicine, and other areas recently working with EDA, it is timely to summarize and review the recent developments and provide an updated and synthesized framework for all researchers interested in incorporating EDA into their research.

中文翻译：

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皮肤电活动数据收集和信号处理的创新：系统评价。

皮肤电活动 (EDA) 信号是汗腺交感神经支配的电表现。EDA 自 1879 年以来就有心理生理​​学（包括情绪或认知压力）研究的历史，但直到最近几年，研究人员才开始将 EDA 用于病理生理学应用，例如评估疲劳、疼痛、嗜睡、运动恢复、癫痫、神经病的诊断、抑郁症等。EDA 新设备和应用的出现促进了新型信号处理技术的发展，创造了越来越多从 EDA 数学导出的测量方法。多年来，简单地计算一段时间内 EDA 值的平均值就可以用来评估觉醒程度。很久以后，研究人员发现 EDA 不仅包含平均值所代表的缓慢变化（紧张成分）的信息，而且还包含信号的快速或阶段性变化的信息。随后出现的技术旨在提供更复杂的 EDA 分析，超越传统的信号主音/相位分解。最近，来自社会科学、工程、医学和其他领域的许多研究人员都在使用 EDA，现在是时候总结和回顾最近的发展，并为所有有兴趣将 EDA 纳入其研究的研究人员提供一个更新和综合的框架。