Interpretation of ETC in the Context of Biomedical Signal Analysis

Effort-To-Compress (ETC) has been proposed earlier as a compression complexity measure for analysing regularity of time-series data. It is a measure of effort to compress an input time series using a lossless compression algorithm known as “Non-Sequential Recursive Pair Substitution”, ETC has been demonstrated as a useful measure for characterizing time series, especially, biomedical signals. Few examples of ETC's applications to biomedical time series include blood flow analysis in human skin, analysis of heart rate variability, complexity analysis of consciousness, classification of corona viruses, and many more. However, the interpretation and relationship of ETC to classical signal parameters is still missing. We address this gap in this study by applying ETC for characterizing synthetic signals that emulate biomedical signals. We also compare the results obtained with Lempel-Ziv complexity, a popular measure that is widely used for biomedical signal analysis.