Decomposition of skin conductance data by means of nonnegative deconvolution
PsychophysiologyPublished 1 March 2010Open access
Mathias Benedek, Christian Kaernbach
Citations590
SJR quartileQ1
SJR score1.26
SNIP1.22
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TL;DR
A two-compartment diffusion model was found to adequately describe a standard SCR shape based on the process of sweat diffusion and nonnegative deconvolution is used to decompose SC data into discrete compact responses.
Abstract
Skin conductance (SC) data are usually characterized by a sequence of overlapping phasic skin conductance responses (SCRs) overlying a tonic component. The variability of SCR shapes hereby complicates the proper decomposition of SC data. A method is proposed for full decomposition of SC data into tonic and phasic components. A two-compartment diffusion model was found to adequately describe a standard SCR shape based on the process of sweat diffusion. Nonnegative deconvolution is used to decompose SC data into discrete compact responses and at the same time assess deviations from the standard SCR shape, which could be ascribed to the additional process of pore opening. Based on the result of single non-overlapped SCRs, response parameters can be estimated precisely as shown in a paradigm with varying inter-stimulus intervals.
Keywords
Agricultural and Biological SciencesNeuroscience
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