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Title: PySiology : a python package for physiological feature extraction
Authors: Gabrieli, Giulio
Azhari, Atiqah
Esposito, Gianluca
Keywords: Social sciences::Psychology
Issue Date: 2019
Publisher: Springer, Singapore
Source: Gabrieli G., Azhari A., & Esposito G. (2020). PySiology : a python package for physiological feature extraction. In A. Esposito, M. Faundez-Zanuy, F. C. Morabito, & E. Pasero (Eds.), Neural Approaches to Dynamics of Signal Exchanges (pp. 394-402). doi:10.1007/978-981-13-8950-4_35
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.
ISBN: 978-981-13-8949-8
DOI: 10.1007/978-981-13-8950-4_35
Rights: © 2020 Springer Nature Singapore Pte Ltd. All rights reserved. This book is made available with permission of Springer Nature Singapore Pte Ltd.
Fulltext Permission: embargo_20210926
Fulltext Availability: With Fulltext
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