PySiology : a python package for physiological feature extraction
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 tool...
| Main Authors: | , , |
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| Format: | Book Chapter |
| Language: | English |
| Published: |
Springer, Singapore
2020
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| Online Access: | https://hdl.handle.net/10356/143582 |
| _version_ | 1824453396082458624 |
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| author | Gabrieli, Giulio Azhari, Atiqah Esposito, Gianluca |
| author2 | Esposito, Anna |
| author_facet | Esposito, Anna Gabrieli, Giulio Azhari, Atiqah Esposito, Gianluca |
| author_sort | Gabrieli, Giulio |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T07:59:40Z |
| format | Book Chapter |
| id | ntu-10356/143582 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:59:40Z |
| publishDate | 2020 |
| publisher | Springer, Singapore |
| record_format | dspace |
| spelling | ntu-10356/1435822020-09-10T08:00:09Z PySiology : a python package for physiological feature extraction Gabrieli, Giulio Azhari, Atiqah Esposito, Gianluca Esposito, Anna Faundez-Zanuy, Marcos Morabito, Francesco Carlo Pasero, Eros School of Social Sciences Social sciences::Psychology Physiology Signal processing 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. Accepted version 2020-09-10T08:00:09Z 2020-09-10T08:00:09Z 2019 Book Chapter 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_35 978-981-13-8949-8 https://hdl.handle.net/10356/143582 10.1007/978-981-13-8950-4_35 395 402 en Neural Approaches to Dynamics of Signal exchanges © 2020 Springer Nature Singapore Pte Ltd. All rights reserved. This book is made available with permission of Springer Nature Singapore Pte Ltd. application/pdf Springer, Singapore |
| spellingShingle | Social sciences::Psychology Physiology Signal processing Gabrieli, Giulio Azhari, Atiqah Esposito, Gianluca PySiology : a python package for physiological feature extraction |
| title | PySiology : a python package for physiological feature extraction |
| title_full | PySiology : a python package for physiological feature extraction |
| title_fullStr | PySiology : a python package for physiological feature extraction |
| title_full_unstemmed | PySiology : a python package for physiological feature extraction |
| title_short | PySiology : a python package for physiological feature extraction |
| title_sort | pysiology a python package for physiological feature extraction |
| topic | Social sciences::Psychology Physiology Signal processing |
| url | https://hdl.handle.net/10356/143582 |
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