[1]
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A novel technique for the detection of myocardial dysfunction using ECG signals based on CEEMD, DWT, PSR and neural networks
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Artificial Intelligence …,
2022 |
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[2]
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Phase irregularity: A conceptually simple and efficient approach to characterize electroencephalographic recordings from epilepsy patients
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Physical Review E,
2022 |
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[3]
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Myocardial infarction detection using ITD, DWT and deterministic learning based on ECG signals
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Cognitive Neurodynamics,
2022 |
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[4]
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Emotion Recognition Method Based on EEG in Few Channels
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2022 IEEE 11th Data …,
2022 |
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[5]
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Biomedical Signal Data Features Dimension Reduction Using Linear Discriminant Analysis and Threshold Classifier in Case of Two Multidimensional Classes
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Brazilian Congress on Biomedical Engineering,
2022 |
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[6]
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Weighted complex network based framework for epilepsy detection from EEG signals
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2020 |
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[7]
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Myocardial infarction detection using artificial intelligence and nonlinear features based on synthesis of the standard 12-lead and Frank XYZ leads
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2020 |
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[8]
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Feature Extraction of Surface Electromyography Using Wavelet Weighted Permutation Entropy for Hand Movement Recognition
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2020 |
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[9]
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Identification of epileptic seizures in EEG signals using time-scale decomposition (ITD), discrete wavelet transform (DWT), phase space reconstruction (PSR) and …
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2019 |
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[10]
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Seizure and Non-Seizure EEG Signals Detection Using 1-D Convolutional Neural Network Architecture of Deep Learning Algorithm
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2019 |
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[11]
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Wavelet Analysis of EEG Signals in Epilepsy Patients
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2019 |
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[12]
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EEG işaretlerinin epileptik nöbet kestiriminde modern yöntemlerle analizi ve sınıflandırılması
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2018 |
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[13]
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Epileptic seizure anticipation and localisation of epileptogenic region using EEG signals
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Journal of Medical Engineering & Technology,
2018 |
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[14]
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Correction to: Classification of Normal, Ictal and Inter-ictal EEG via Direct Quadrature and Random Forest Tree
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2018 |
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[15]
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Noninvasive method of epileptic detection using DWT and generalized regression neural network
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2018 |
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[16]
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Accuracy Enhancement of the Epileptic Seizure Diseases Detection in EEG Signals
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2017 |
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[17]
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Comparison of different classification methods for the preictal stage detection in EEG signals
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2017 |
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[18]
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Monitoring Depth of Anesthesia Using Detrended Fluctuation Analysis Based on EEG Signals
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Journal of Medical and Biological Engineering,
2017 |
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[19]
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A versatile EEG spike detector with multivariate matrix of features based on the linear discriminant analysis, combined wavelets, and descriptors
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Pattern Recognition Letters,
2017 |
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[20]
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Classification of Normal, Ictal and Inter-ictal EEG via Direct Quadrature and Random Forest Tree
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Journal of Medical and Biological Engineering,
2017 |
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[21]
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Symbolic Analysis of Brain Dynamics Detects Negative Stress
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Entropy,
2017 |
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[22]
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Multiple entropies performance measure for detection and localization of multi-channel epileptic EEG
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Biomedical Signal Processing and Control,
2017 |
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[23]
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Accuracy Enhancement of the Epileptic Seizure Detection in EEG Signals
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2017 |
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[24]
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基于支持向量机的驾驶精神疲劳分级
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武警工程大学学报,
2016 |
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[25]
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A Numerical Study of Information Entropy in EEG Wavelet Analysis
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2016 |
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[26]
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Dalgacık Dönüşümü ve Ampirik Mod Ayrışımı Tabanlı Özelliklerin Epileptik Nöbet Algılama Performanslarının Karşılaştırılması
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2016 |
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[27]
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Assessing heart rate variability through wavelet-based statistical measures
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Computers in Biology and Medicine,
2016 |
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[28]
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Comparison of Seizure Detection Performances of Features Based on Wavelet Transform and Empirical Mode Decomposition
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Journal of New Results in Science (JNRS),
2016 |
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[29]
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A novel method of EEG data acquisition, feature extraction and feature space creation for early detection of epileptic seizures
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2016 |
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[30]
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Influences of the signal border extension in the discrete wavelet transform in EEG spike detection
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2016 |
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[31]
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基于脑电信号的麻醉特征参数分析
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生物医学工程学杂志,
2015 |
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[32]
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A hybrid automated detection of epileptic seizures in EEG records
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Computers & Electrical Engineering,
2015 |
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[33]
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A low-power analog-signal-processing-unit for wirelessly-powered implantable recording system
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2014 |
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[34]
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Characterization of EEG signals for identification of alcoholics using ANOVA ranked approximate entropy and classifiers
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Circuits, Communication, Control and Computing (I4C), 2014 International Conference on,
2014 |
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[35]
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A high accuracy continuous wavelet function approximation for implantable device applications
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Electrical and Computer Engineering (ICECE), 2014 International Conference on,
2014 |
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[36]
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Analysis of EEG Signals Related to Artists and Nonartists during Visual Perception, Mental Imagery, and Rest Using Approximate Entropy
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BioMed research international,
2014 |
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[37]
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Chaotic analysis of the human brain cortical model and robust control of epileptic seizures using sliding mode control
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Systems Science & Control Engineering: An Open Access Journal,
2014 |
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[38]
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Anticipation des crises d'épilepsie temporale combinant des méthodes statistiques et non-linéaires d'analyse d'électroencéphalographie
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NULL
2014 |
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[39]
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EEG Subband Analysis using Approximate Entropy for the Detection of Epilepsy
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IOSR Journal of Computer Engineering (IOSR-JCE),
2014 |
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[40]
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MF-DFA 在癫痫发作期及发作强度检测中的应用
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数据采集与处理,
2013 |
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[41]
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Effects of subject's wakefulness state and health status on approximated entropy during eye opening and closure test of routine EEG examination
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Journal of Biomedical Science and Engineering,
2012 |
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[42]
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Automatic Seizure Detection Based on Wavelet-Chaos Methodology from EEG and its Sub-bands
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A Abbaspour, A Kashaninia, M Amiri - khuisf.ac.ir,
2011 |
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[43]
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An Efficient Classification of EEG Signals for Epilepsy based on Discrete Wavelet Transform and Approximate Entropy using Constrained Neyman-Pearson Criteria
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Digital Signal Processing,
2011 |
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