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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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.
DepartmentMassachusetts Institute of Technology. Media Laboratory; Program in Media Arts and Sciences (Massachusetts Institute of Technology)
2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Institute of Electrical and Electronics Engineers (IEEE)
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.
Author's final manuscript