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...
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| Main Authors: | , , |
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| Other Authors: | |
| Format: | Book Chapter |
| Language: | English |
| Published: |
Springer, Singapore
2020
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/143582 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | 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. |
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