Results 231 to 240 of about 10,393 (254)
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Adaptive Multiscale Entropy Analysis of Multivariate Neural Data
IEEE Transactions on Biomedical Engineering, 2012Multiscale entropy (MSE) has been widely used to quantify a system's complexity by taking into account the multiple time scales inherent in physiologic time series. The method, however, is biased toward the coarse scale, i.e., low-frequency components due to the progressive smoothing operations.
Meng Hu, Hualou Liang
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Hypoglycemia-Related Electroencephalogram Changes Assessed by Multiscale Entropy
Diabetes Technology & Therapeutics, 2014Background: Several clinical studies have shown that low blood glucose (BG) levels affect electroencephalogram (EEG) rhythms through the quantification of traditional indicators based on linear spectral analysis.
FABRIS, CHIARA +7 more
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[Multiscale entropy analysis of electrocardiogram].
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi, 2009Using the algorithm proposed by Costa M, et al., we studied the multiscale entropy (MSE) of electrocardiogram. The sample entropy (SampEn) of the healthy subjects was found to be higher than that of the subjects with coronary heart disease or myocardial infarction. The healthy subjects' complexity was found to be the highest. The SampEn of the subjects
Jun, Wang +5 more
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Entropy estimation and multiscale processing in meteorological satellite images
Object recognition supported by user interaction for service robots, 2003A new model for the multiscale characterization of turbulence and chaotic information in digital images is presented. The model is applied to infrared satellite images for the determination of specific areas inside the clouds. These images are difficult to manipulate however due to their intrinsically chaotic character, consequence of the extreme ...
Turiel, A., Grazzini, J., Yahia, H.
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Multiscale Entropy Analysis of Artifactual EEG Recordings
2011Electroencephalographic (EEG) recordings are employed in order to investigate the brain activity in neuropathological subjects, but unfortunately EEG are often contaminated by artifacts, signals that have no-cerebral origin and therefore distort the EEG analysis.
Domenico Labate +3 more
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Multivariate Multiscale Cosine Similarity Entropy
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022Hongjian Xiao +2 more
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Multiscale entropy in a 10-minute vigilance task
International Journal of PsychophysiologyResearch has shown multiscale entropy, brain signal behavior across time scales, to reliably increase at lower time scales with time-on-task fatigue. However, multiscale entropy has not been examined in short vigilance tasks (i.e., ≤ 10 min). Addressing this gap, we examine multiscale entropy during a 10-minute Psychomotor Vigilance Test (PVT).
L Jack, Rhodes +2 more
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Multiscale entropy rates: A study on different stochastic processes
Digital Signal ProcessingIn this paper, we propose to analyze the behavior of the entropy rate (ER) when applied to a signal and its coarse-grained versions. The “multiscale entropy rate” (MSER) is deduced by storing in a vector the resulting ERs. Our contribution consists in studying the MSER calculated on different stochastic processes.
Éric Grivel +2 more
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Multiscale Fuzzy Entropy-Based Feature Selection
IEEE Transactions on Fuzzy Systems, 2023Zhihong Wang 0001 +4 more
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Multiscale Entropy Rate: A Variant of the Multiscale Entropy
2024 32nd European Signal Processing Conference (EUSIPCO)Eric J. Grivel +2 more
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