Abstract
BackgroundEntropy analysis has been attracting increasing attentions in the recent two or three decades. It assesses complexity, or irregularity, of time-series which is extraordinarily relevant to physiology and diseases as demonstrated by tremendous studies. However, the complexity can hardly be appreciated by traditional methods including time-, frequency-domain analysis, and time-frequency analysis that are the common built-in options in commercialized measurement and statistical software. To facilitate the entropy analysis of physiological time-series, a new software application, namely EZ Entropy, was developed and introduced in this article.ResultsEZ Entropy was developed in MATLAB® environment. It was programmed in an object-oriented style and was constructed with a graphical user interface. EZ Entropy is easy to operate through its compact graphical interface, thus allowing researchers without knowledge of programming like clinicians and physiologists to perform such kind of analysis. Besides, it offers various settings to meet different analysis needs including (1) processing single data recording, (2) batch processing multiple data files, (3) sliding window calculations, (4) recall, (5) displaying intermediate data and final results, (6) adjusting input parameters, and (7) exporting calculation results after the run or in real-time during the analysis. The analysis results could be exported, either manually or automatically, to comma-separated ASCII files, thus being compatible to and easily imported into the common statistical analysis software. Code-wise, EZ Entropy is object-oriented, thus being quite easy to maintain and extend.ConclusionsEZ Entropy is a user-friendly software application to perform the entropy analysis of time-series, as well as to simplify and to speed up this useful analysis.
Highlights
Entropy analysis has been attracting increasing attentions in the recent two or three decades
In the most recent two or three decades, researchers from interdisciplinary fields have proposed the concept of nonlinear dynamical analysis, and from on lines of evidence have demonstrated the unique power of various nonlinear dynamical characteristics in this regard [1,2,3,4]
Many researchers have published or shared open-source codes either in formal publications [14] or in various online repositories [18,19,20,21,22,23,24], neither of them is really user-friendly as it still requires users to have at least some basic coding training in order to apply these codes. The aim of this current work was to introduce a graphical interface-based software application, namely EZ Entropy, which was dedicatedly developed for the purposes of calculating the entropy of physiological time-series
Summary
Entropy analysis has been attracting increasing attentions in the recent two or three decades. It assesses complexity, or irregularity, of time-series which is extraordinarily relevant to physiology and diseases as demonstrated by tremendous studies. The complexity can hardly be appreciated by traditional methods including time-, frequency-domain analysis, and time-frequency analysis that are the common built-in options in commercialized measurement and statistical software. Results: EZ Entropy was developed in MATLAB® environment It was programmed in an object-oriented style and was constructed with a graphical user interface. It is a contemporary challenge to identify characteristics from physiological signals or time-series that are relevant to aging or disease progression. In the most recent two or three decades, researchers from interdisciplinary fields have proposed the concept of nonlinear dynamical analysis, and from on lines of evidence have demonstrated the unique power of various nonlinear dynamical characteristics in this regard [1,2,3,4]
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