ORCID: orcid.org/0000-0002-4822-5562

SCOPUS: https://www.scopus.com/authid/detail.uri?authorId=56854902700&eid=2-...

SCHOLAR: https://scholar.google.it/citations?user=Buhja1IAAAAJ&hl=it

Department of Information Engineering

Faculty of Engineering, University of Pisa

Via G. Caruso 5 - 56122 - Pisa -  Italy

Tel.+39 050 2217462

cvxEDA Model: a  Convex Optimization Approach to Electrodermal Activity Processing

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 cvxEDA 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 artefacts. 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 to properly describe the activity of the autonomic nervous system in response to strong affective stimulation. Results are very encouraging, showing the excellent performance of the proposed method and suggesting several applications in psychological, clinical, biomedical, and affective computing research fields.

cvxEDA code:    https://github.com/lciti/cvxEDA    OR     https://it.mathworks.com/matlabcentral/fileexchange/53326-cvxeda

cvxEDA article: https://www.researchgate.net/publication/270588614_cvxEDA_A_Convex_Optim...