PySiology: A Python Package for Physiological Feature Extraction

Giulio Gabrieli, Atiqah Azhari, Gianluca Esposito

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Physiological signals have been widely used to measure continuous data from the autonomic nervous system in the fields of computer science, psychology, and human–computer interaction. Signal processing and feature estimation of physiological measurements can be performed with several commercial tools. Unfortunately, those tools possess a steep learning curve and do not usually allow for complete customization of estimation parameters. For these reasons, we designed PySiology, an open-source package for the estimation of features from physiological signals, suitable for both novice and expert users. This package provides clear documentation of utilized methodology, guided functionalities for semi-automatic feature estimation, and options for extensive customization. In this article, a brief introduction to the features of the package, and to its design workflow, are presented. To demonstrate the usage of the package in a real-world context, an advanced example of image valence estimation from physiological measurements (ECG, EMG, and EDA) is described. Preliminary tests have shown high reliability of feature estimated using PySiology.

Original languageEnglish
Title of host publicationSmart Innovation, Systems and Technologies
PublisherSpringer Science and Business Media Deutschland GmbH
Pages395-402
Number of pages8
DOIs
Publication statusPublished - 2020

Publication series

NameSmart Innovation, Systems and Technologies
Volume151
ISSN (Print)2190-3018
ISSN (Electronic)2190-3026

Keywords

  • Heart rate variability
  • Physiology
  • Signal processing

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