Wavelet-based motion artifact removal for electrodermal activity
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Picard_Wavelet-based.pdf
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201.93 KB
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Author(s)
Chen, Weixuan
Jaques, Natasha Mary
Taylor, Sara Ann
Sano, Akane
Fedor, Szymon
Picard, Rosalind W.
Date Issued
October 2015
Journal
2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Weixuan Chen et al. “Wavelet-Based Motion Artifact Removal for Electrodermal Activity.” 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 25-29 August, 2015, Milan, Italy, IEEE, 2015.
Version
Author's final manuscript
Abstract
Electrodermal activity (EDA) recording is a powerful, widely used tool for monitoring psychological or physiological arousal. However, analysis of EDA is hampered by its sensitivity to motion artifacts. We propose a method for removing motion artifacts from EDA, measured as skin conductance (SC), using a stationary wavelet transform (SWT). We modeled the wavelet coefficients as a Gaussian mixture distribution corresponding to the underlying skin conductance level (SCL) and skin conductance responses (SCRs). The goodness-of-fit of the model was validated on ambulatory SC data. We evaluated the proposed method in comparison with three previous approaches. Our method achieved a greater reduction of artifacts while retaining motion-artifact-free data.
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/EMBC.2015.7319814
