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Signal and System

Signal and System

A signal x(t) is a set of data or a time function representing a variable of interest. Signals typically convey information about a phenomenon, such as atmospheric temperature, humidity, human voice, television images, a dog's bark, or birdsongs. More generally, a signal can be a function of more than one independent variable. For instance, images depend on horizontal and vertical positions and can be regarded as two-dimensional signals. However, this text will focus on one-dimensional...

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Physiological signal analysis and open science using the Julia language and associated software.

George Datseris¹, Jacob S Zelko^2,3

¹Department of Mathematics and Statistics, University of Exeter, Exeter, United Kingdom.

Frontiers in Network Physiology

|November 21, 2024

Summary

Julia programming offers reproducible, efficient, and sustainable physiological signal analysis. Its open-source ecosystem and package manager facilitate code sharing and reusable, cross-platform projects for scientific research.

Keywords:

Julia complexity measures digital signal processing open science physiological signals reproducible time series analysis

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Area of Science:

Computational Biology
Biomedical Engineering
Scientific Computing

Background:

Physiological signal analysis is crucial in biomedical research.
Current methods may face challenges in reproducibility and efficiency.
The need for robust and sustainable software solutions is growing.

Purpose of the Study:

To propose the Julia programming language for physiological signal analysis.
To highlight Julia's suitability for reproducible, efficient, and sustainable research.
To showcase available Julia software and community support for signal processing.

Main Methods:

Review of existing Julia software and algorithms for physiological signal processing.
Discussion of Julia's language features supporting high performance and interactivity.
Analysis of Julia's ecosystem for open and reproducible science.

Main Results:

Julia provides top-tier algorithms for physiological signal processing.
Its high-level, interactive nature accelerates research and development.
Julia's open-source nature and package manager promote code sharing and reuse.
Easy creation of self-contained, reproducible projects across different platforms.

Conclusions:

Julia is a strong candidate for reproducible, efficient, and sustainable physiological signal analysis.
The Julia ecosystem fosters open science principles and community contributions.
Its package manager simplifies the creation and deployment of reproducible research software.