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Innovations in Electrodermal Activity Data Collection and Signal Processing: A Systematic Review.
Hugo F Posada-Quintero1, Ki H Chon1
1Department of Biomedical Engineering, University of Connecticut, Storrs, CT 06269, USA.
Sensors (Basel, Switzerland)
|January 19, 2020
Summary
Electrodermal activity (EDA) research has expanded from psychophysiology to diverse medical applications. Recent advancements focus on sophisticated signal processing techniques for a more comprehensive understanding of EDA measures.
Area of Science:
- Physiology
- Biomedical Engineering
- Psychophysiology
Background:
- Electrodermal activity (EDA) reflects sympathetic nervous system activity via sweat glands.
- Historically used in psychophysiology for stress, EDA is now applied to various pathophysiological conditions.
- Novel devices and signal processing techniques are expanding EDA's utility.
Purpose of the Study:
- To review recent developments in electrodermal activity (EDA) research.
- To synthesize an updated framework for researchers utilizing EDA.
- To highlight advanced signal processing techniques beyond traditional tonic/phasic analysis.
Main Methods:
- Review of recent literature on electrodermal activity (EDA) signal processing.
- Synthesis of emerging EDA measures and their applications.
- Exploration of advanced mathematical derivations from EDA signals.
Main Results:
- EDA analysis has evolved from simple mean values to complex signal processing.
- New techniques capture both tonic and phasic components of EDA for richer insights.
- A growing body of research utilizes EDA for medical and physiological assessments.
Conclusions:
- EDA is a valuable tool with expanding applications in medicine and physiology.
- Advanced signal processing offers deeper insights into the information contained within EDA signals.
- An updated framework is needed to guide interdisciplinary researchers using EDA.
