Conference proceeding
Electrodermal Activity in Ambulatory Settings: A Narrative Review of Literature
Advances in Neuroergonomics and Cognitive Engineering , v 953, pp 91-102
01 Jan 2020
Abstract
Electrodermal activity (EDA) is a portable, non-invasive and wearable sensor that measures skin electrical properties to track correlates of autonomic nervous system activity. Although EDA utilization is sparse compared to some other biomedical signals in ambulatory settings, it can be a potentially helpful adjunct tool in neuroergonomics studies and mobile brain and body research. This paper summarizes EDA physiological principles and methodology including data acquisition, signal processing, and data analysis approaches. In addition, use of EDA in diverse neuroergonomic application areas, such as in psychiatry, neurology, operator and consumer assessment, virtual reality and gaming have been outlined.
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Details
- Title
- Electrodermal Activity in Ambulatory Settings: A Narrative Review of Literature
- Creators
- Yigit Topoglu (Corresponding Author) - Drexel UniversityJan Watson - Drexel UniversityRajneesh Suri - Drexel UniversityHasan Ayaz - Drexel University
- Contributors
- H Ayaz (Editor) - Drexel University
- Publication Details
- Advances in Neuroergonomics and Cognitive Engineering , v 953, pp 91-102
- Conference
- AHFE 2019 International Conference on Neuroergonomics and Cognitive Engineering, and the AHFE International Conference on Industrial Cognitive Ergonomics and Engineering Psychology (Washington, District of Columbia, United States, 24 Jul 2019–2019)
- Series
- Advances in Intelligent Systems and Computing; 953
- Publisher
- Springer Nature
- Number of pages
- 12
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Bennett S. LeBow College of Business; School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:000502759200010
- Scopus ID
- 2-s2.0-85067665568
- Other Identifier
- 991019167784704721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Neurosciences