Greco, A and Valenza, G and Lanata, A and Scilingo, EP and Citi, L (2016) 'cvxEDA: a Convex Optimization Approach to Electrodermal Activity Processing.' IEEE Transactions on Biomedical Engineering, 63 (4). 797 - 804. ISSN 0018-9294

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Abstract

This paper reports on a novel algorithm for the analysis of electrodermal activity (EDA) using methods of convex optimization. EDA can be considered one of the most common observation channels of sympathetic nervous system activity, and manifests itself as a change in electrical properties of the skin, such as skin conductance (SC). The proposed model describes SC as the sum of three terms: the phasic component, the tonic component, and an additive white Gaussian noise term incorporating model prediction errors as well as measurement errors and artifacts. This model is physiologically inspired and fully explains EDA through a rigorous methodology based on Bayesian statistics, mathematical convex optimization and sparsity. The algorithm was evaluated in three different experimental sessions to test its robustness to noise, its ability to separate and identify stimulus inputs, and its capability of properly describing the activity of the autonomic nervous system in response to strong affective stimulation. Results are very encouraging, showing good performance of the proposed method and suggesting promising future applicability, e.g. in the field of affective computing.

Item Type:	Article
Uncontrolled Keywords:	Convex optimization; electrodermal activity; skin conductance; sparse deconvolution
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User:	Luca Citi
Date Deposited:	01 Sep 2015 08:13
Last Modified:	08 Jul 2018 12:15
URI:	http://repository.essex.ac.uk/id/eprint/14731

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• cvxEDA: a Convex Optimization Approach to Electrodermal Activity Processing. (deposited 01 Sep 2015 08:13) [Currently Displayed]

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