A Systematic Method for Preprocessing and Analyzing Electrodermal Activity
Name
EMBC 2019 Draft Ver 7.pdf
Size
1.38 MB
Format
Adobe PDF
Checksum (MD5)
38a8d13ae06ea1b9214bf3ec64532242
Author(s)
Subramanian, Sandya
Barbieri, Riccardo
Brown, Emery Neal
Date Issued
October 2019
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
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.
MIT Department
Harvard University--MIT Division of Health Sciences and Technology
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/embc.2019.8857757
