Applying Improved Multiscale Fuzzy Entropy for Feature Extraction of MI-EEG [PDF]
Applied Sciences (Switzerland), 2017 Electroencephalography (EEG) is considered the output of a brain and it is a bioelectrical signal with multiscale and nonlinear properties. Motor Imagery EEG (MI-EEG) not only has a close correlation with the human imagination and movement intention but ...
Mingai Li, Hai-Na Liu, Jin-Fu Yang
exaly +4 more sources
Refined multiscale fuzzy entropy based on standard deviation for biomedical signal analysis [PDF]
Medical and Biological Engineering and Computing, 2017 Multiscale entropy (MSE) has been a prevalent algorithm to quantify the complexity of fluctuations in the local mean value of biomedical time series. Recent developments in the field have tried to improve the MSE by reducing its variability in large scale factors. On the other hand, there has been recent interest in using other statistical moments than
Hamed Azami +2 more
exaly +7 more sources
Multiscale Entropy Analysis of Short Signals: The Robustness of Fuzzy Entropy-Based Variants Compared to Full-Length Long Signals [PDF]
Entropy, 2021 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.
Airton Monte Serrat Borin +3 more
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A Multivariate Multiscale Fuzzy Entropy Algorithm with Application to Uterine EMG Complexity Analysis [PDF]
Entropy, 2016 The recently introduced multivariate multiscale entropy (MMSE) has been successfully used to quantify structural complexity in terms of nonlinear within- and cross-channel correlations as well as to reveal complex dynamical couplings and various degrees ...
Mosabber U. Ahmed +3 more
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Quantifying Heart Rate Variability Using Multiscale Fuzzy Dispersion Entropy
IEEE AccessHeart rate variability (HRV), which is the variation of inter-beat intervals, exhibits complex characteristics on multiple temporal scales due to the balancing function of the autonomic nervous system.
Chae-Min Kim, Young-Seok Choi
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Recognition of Biological Tissue Denaturation Based on Improved Multiscale Permutation Entropy and GK Fuzzy Clustering [PDF]
Information, 2022 Recognition of biological tissue denaturation is a vital work in high-intensity focused ultrasound (HIFU) therapy. Multiscale permutation entropy (MPE) is a nonlinear signal processing method for feature extraction, widely applied to the recognition of ...
Ziqi Peng, Xian Zhang, Jing Cao, Bei Liu
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An Improved Composite Multiscale Fuzzy Entropy for Feature Extraction of MI-EEG. [PDF]
Entropy (Basel), 2020 Motor Imagery Electroencephalography (MI-EEG) has shown good prospects in neurorehabilitation, and the entropy-based nonlinear dynamic methods have been successfully applied to feature extraction of MI-EEG. Especially based on Multiscale Fuzzy Entropy (MFE), the fuzzy entropies of the τ coarse-grained sequences in τ scale are calculated and averaged to
Li M, Wang R, Xu D.
europepmc +5 more sources
Fractal and FractionalThis paper presents an intelligent fault identification approach integrating composite multiscale fractional fuzzy diversity entropy (CMFFDE) for feature extraction, joint mutual information (JMI) for feature selection, and an extreme learning machine ...
Xiong Gan, Guangyou Yang
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Evaluation of entropy features and classifier performance in person authentication using resting-state EEG [PDF]
Frontiers in NeuroscienceIntroductionResting-state electroencephalogram (EEG) presents a promising biometric modality due to its inherent liveness detection and resistance to spoofing, addressing critical vulnerabilities in conventional systems.
Renyu Yang +8 more
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Multiscale fuzzy entropy based on local mean decomposition and Fisher rule for EEG feature extraction in human motion analysis [PDF]
EAI Endorsed Transactions on Scalable Information Systems, 2022 Electroencephalogram (EEG) is a nonlinear, non-stationary, and random weak signal generated by a large number of neurons. It has great research value and practical significance in artificial intelligence, biomedical engineering
Huili He
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