pyphysio: A physiological signal processing library for data science approaches in physiology

被引:42
作者
Bizzego, Andrea [1 ]
Battisti, Alessandro [2 ]
Gabrieli, Giulio [3 ]
Esposito, Gianluca [1 ,3 ]
Furlanello, Cesare [2 ]
机构
[1] Univ Trento, Trento, Italy
[2] Fdn Bruno Kessler, Povo, Italy
[3] Nanyang Technol Univ, Singapore, Singapore
关键词
Physiological signal processing; Psychophysiology; Autonomic indicators; Data science; !text type='Python']Python[!/text; RATE-VARIABILITY ANALYSIS; RESPONSES;
D O I
10.1016/j.softx.2019.100287
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
The lack of open-source tools for physiological signal processing hinders the development of standardized pipelines in physiology. Researchers usually must rely on commercial software that, by implementing black-box algorithms, undermines the control on the analysis and prevents the comparison of the results, ultimately affecting the scientific reproducibility. We introduce pyphysio as a step towards a data science approach oriented to compute physiological indicators, in particular of the Autonomic Nervous System activity. pyphysio serves as a basis for machine learning modules and it implements a suite of combinable algorithms for processing of signals from either by wearable or medical-grade quality devices. (C) 2019 Published by Elsevier B.V.
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页数:5
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