Journal of Physical Chemistry & Biophysics
Open Access
ISSN: 2161-0398
+44 1478 350008
ISSN: 2161-0398
+44 1478 350008
Airton
University of frence, Brazil
Scientific Tracks Abstracts: J Phys Chem Biophys
Multiscale entropy (MSE) analysis is a fundamental approach to access the complexity of a time series by estimating its information creation over a range of temporal scales. However, MSE may not be accurate or valid for short time series. This is why previous studies applied different kinds of algorithm derivations to short-term time series. However, no study has systematically analyzed and compared their reliabilities. This study compares the MSE algorithm variations adapted to short time series on both human and rat heart rate variability (HRV) time series using long-term MSE as reference. The most used variations of MSE are studied: composite MSE (CMSE), refined composite MSE (RCMSE), modified MSE (MMSE), and their fuzzy versions. We also analyze the errors in MSE estimations for a range of incorporated fuzzy exponents. The results show that fuzzy MSE versions—as a function of time series length—present minimal errors compared to the non-fuzzy algorithms. The traditional multiscale entropy algorithm with fuzzy counting (MFE) has similar accuracy to alternative algorithms with better computing performance. For the best accuracy, the findings suggest different fuzzy exponents according to the time series length.
Airton Monte Serrat Borin Junior holds a degree in Mathematics from the University of Franca (2001), a Master's in Mathematics from the Federal University of Triângulo Mineiro (2011) and a Ph.D. in Physics Applied to Medicine and Biology (FAMB) from the University of São Paulo (2021) . He is currently Professor of Basic, Technical and Technological Education at the Triângulo Mineiro Campus Uberaba Federal Institute, working in the area of Mathematics. My current line of research is nonlinear processing and analysis of short duration time series.