Estimation of Skin Conductance Response Through Adaptive Filtering

  • Pietro SavazziEmail author
  • Floriana Vasile
  • Natascia Brondino
  • Marco Vercesi
  • Pierluigi Politi
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 297)


The importance of medical wearable sensors is increasing in aiding both diagnostic and therapeutic protocols, in a wide area of health applications. Among them, the acquisition and analysis of electrodermal activity (EDA) may help in detecting seizures and different human emotional states. Nonnegative deconvolution represents an important step needed for decomposing the measured galvanic skin response (GSR) in its tonic and phasic components. In particular, the phasic component, also known as skin conductance response (SCR), is related to the sympathetic nervous system (SNS) activity, since it can be modeled as the linear convolution between the SCR driver events, modeled by sparse impulse signals, with an impulse response representing the sudomotor SNS innervation. In this paper, we propose a novel method for implementing this deconvolution by an adaptive filter, determined by solving a linear prediction problem, which results independent on the impulse response parameters, usually represented by sampling the biexponential Bateman function. The performance of the proposed approach is evaluated by using both synthetic and experimental data.


Galvanic skin response Electrodermal activity Skin conductance response Adaptive filter Wearable sensor 


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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019

Authors and Affiliations

  1. 1.Department of Electrical, Computer and Biomedical EngineeringUniversity of PaviaPaviaItaly
  2. 2.Department of Brain and Behavioral SciencesUniversity of PaviaPaviaItaly

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