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Wavelet-based motion artifact removal for electrodermal activity

Author(s)
Chen, Weixuan; Jaques, Natasha Mary; Taylor, Sara Ann; Sano, Akane; Fedor, Szymon; Picard, Rosalind W.; ... Show more Show less
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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.
Date issued
2015-10
URI
http://hdl.handle.net/1721.1/110678
Department
Massachusetts Institute of Technology. Media Laboratory; Program in Media Arts and Sciences (Massachusetts Institute of Technology)
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
ISBN
978-1-4244-9271-8

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