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A Systematic Method for Preprocessing and Analyzing Electrodermal Activity

Author(s)
Subramanian, Sandya; Barbieri, Riccardo; Brown, Emery Neal
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DownloadEMBC 2019 Draft Ver 7.pdf (1.383Mb)
Terms of use
Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/
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Abstract
Electrodermal activity (EDA) is a measure of sympathetic tone using sweat gland activity that has applications in research and clinical medicine. We previously identified never-before-seen statistical structure in EDA. However, there is no systematic method to preprocess and analyze EDA data to capture such statistical structure. Therefore, in this study, we analyzed the data of two healthy volunteers while awake and at rest. We used a systematic process that takes advantage of the tail behavior of various statistical distributions to ensure capturing the point process structure in EDA. We verified the presence of this temporal structure in a new dataset of subjects. Our results demonstrate for the first time that point process structure of EDA pulses can be identified across multiple datasets using a systematic method that is still rooted in the underlying physiology.
Date issued
2019-10
URI
https://hdl.handle.net/1721.1/123299
Department
Harvard University--MIT Division of Health Sciences and Technology
Journal
41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Subramanian, Sandya et al. "A Systematic Method for Preprocessing and Analyzing Electrodermal Activity." 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), July 2019, Berlin, Germany, Institute of Electrical and Electronics Engineers (IEEE), October 2019. © 2019 IEEE
Version: Author's final manuscript
ISBN
9781538613115
ISSN
1558-4615
1557-170X

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