A continuous measure of phasic electrodermal activity

By Mathias Benedek, Christian Kaernbach. Journal of Neuroscience Methods, 2010

1,620 citations recorded by the source corpus.

Electrodermal activity is characterized by the superposition of what appear to be single distinct skin conductance responses (SCRs). Classic trough-to-peak analysis of these responses is impeded by their apparent superposition. A deconvolution approach is proposed, which separates SC data into continuous signals of tonic and phasic activity. The resulting phasic activity shows a zero baseline, and overlapping SCRs are represented by predominantly distinct, compact impulses showing an average duration of less than 2 s. A time integration of the continuous measure of phasic activity is proposed as a straightforward indicator of event-related sympathetic activity. The quality and benefit of the proposed measure is demonstrated in an experiment with short interstimulus intervals as well as by means of a simulation study. The advances compared to previous decomposition methods are discussed.

Subfields: Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/9054fa13b000c26d8ebdc4977d89219448b1e606

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In Cognitive Neuroscience

Citations in the corpus

Don't fear ‘fear conditioning’: Methodological considerations for the design and analysis of studies on human fear acquisition, extinction, and return of fear (2017, positive): “Other methods rely on a decomposition (Ledalab; www.ledalab.de; Benedek and Kaernbach, 2010) or a GLM-based deconvolution approach (PsPM or formerly SCRalyze; http://pspm.”
cvxEDA: A Convex Optimization Approach to Electrodermal Activity Processing (2016, methodology): “In particular, the non-negativity of the SMNA — that [14]”
Evaluating the impact of viewing location on view perception using a virtual environment (2020, methodology): “9 toolbox: a MATLAB-based analysis tool for extracting SCL and SCR values from the SC data, using a continuous decomposition analysis method [89,90].”
Innovations in Electrodermal Activity Data Collection and Signal Processing: A Systematic Review (2020, methodology): “Therefore, EDA is believed to represent a quantitative functional measure of sudomotor activity, and consequently, an objective assessment of arousal [6,7].”