Results 21 to 30 of about 38,961 (295)
Combination of R-R Interval and Crest Time in Assessing Complexity Using Multiscale Cross-Approximate Entropy in Normal and Diabetic Subjects [PDF]
Entropy, 2018 The present study aimed at testing the hypothesis that application of multiscale cross-approximate entropy (MCAE) analysis in the study of nonlinear coupling behavior of two synchronized time series of different natures [i.e., R-R interval (RRI) and ...
Ming-Xia Xiao +4 more
doaj +2 more sources
Entropy, 2017 Heart rate variability (HRV) analysis is a non-invasive tool for assessing cardiac health. Entropy measures quantify the chaotic properties of HRV, but they are sensitive to the choice of their required parameters.
Stefan Hagmair +10 more
doaj +2 more sources
Comparative study of approximate entropy and sample entropy robustness to spikes [PDF]
Artificial Intelligence in Medicine, 2011 There is an ongoing research effort devoted to characterize the signal regularity metrics approximate entropy (ApEn) and sample entropy (SampEn) in order to better interpret their results in the context of biomedical signal analysis. Along with this line, this paper addresses the influence of abnormal spikes (impulses) on ApEn and SampEn measurements.A
David Cuesta-Frau +2 more
exaly +4 more sources
Information sharing among cryptocurrencies: Evidence from mutual information and approximate entropy during COVID-19 [PDF]
Finance Research Letters, 2022 Ata Assaf, Husni Charif, Ender Demir
exaly +2 more sources
Fault Diagnosis of the Bearing based on the Wavelet Transform and Approximate Entropy
Jixie chuandong, 2015 Combining the wavelet transform and approximate entropy theory,according to the characteristic that the approximate entropy will become larger with the increase of signal complexity,it is applied to the analysis of acoustic emission signals of the ...
Zhang Penglin +4 more
doaj +2 more sources
Frontiers in Genetics, 2021 Classification is widely used in gene expression data analysis. Feature selection is usually performed before classification because of the large number of genes and the small sample size in gene expression data.
Hengyi Zhang
doaj +1 more source
Approximation of Entropy Numbers [PDF]
Complex Analysis and Operator Theory, 2019 10 ...
K. P. Deepesh, V. B. Kiran Kumar
openaire +2 more sources
IEEE Access, 2023 An automated Neurological Disorder detection system can be considered as a cost-effective and resource efficient tool for medical and healthcare applications.
S. Janifer Jabin Jui +5 more
doaj +1 more source
Approximate entropy and auto mutual information analysis of the electroencephalogram in Alzheimer's disease patients [PDF]
, 2008 We analysed the electroencephalogram (EEG) from Alzheimer's disease (AD) patients with two nonlinear methods: approximate entropy (ApEn) and auto mutual information (AMI).
Gomez, C. +4 more
core +1 more source
Approximate entropy as an indicator of non-linearity in self paced voluntary finger movement EEG [PDF]
, 2013 This study investigates the indications of non-linear dynamic structures in electroencephalogram signals. The iterative amplitude adjusted surrogate data method along with seven non-linear test statistics namely the third order autocorrelation, asymmetry
Balli, Tugce +2 more
core +1 more source