"A new approach for epileptic seizure detection: sample entropy based feature extraction and extreme learning machine"
written by Yuedong Song, Pietro Liò,
published by Journal of Biomedical Science and Engineering, Vol.3 No.6, 2010
has been cited by the following article(s):
  • Google Scholar
  • CrossRef
[1] Research Review an Automatic Detection of Epilepsy in Human brain signal
International Journal of Advanced Computer Technology (IJACT)
[2] Unsupervised EEG feature extraction based on echo state network
Information Sciences, 2019
[3] Optimized deep neural network architecture for robust detection of epileptic seizures using EEG signals
2019
[4] Neural Network Based Brain Tumor Detection Using Wireless Infrared Imaging Sensor
2019
[5] Automated Epileptic Seizure Detection Method Based on the Multi-attribute EEG Feature Pool and mRMR Feature Selection Method
2019
[6] Entropy-based feature extraction technique in conjunction with wavelet packet transform for multi-mental task classification
2019
[7] Formulation of a Novel Classification Indices for Classification of Human Hearing Abilities According to Cortical Auditory Event Potential signals
2019
[8] Epileptic Seizure Detection and Classification Using Machine Learning
2019
[9] A support vector machine approach for AF classification from a short single-lead ECG recording
2018
[10] Imbalance Learning Using Neural Networks for Seizure Detection
2018
[11] Robust Detection of Epileptic Seizures Using Deep Neural Networks
2018
[12] Brain Data Mining for Epileptic Seizure-Detection
2018
[13] Epileptic Seizure Detection Using Empirical Mode Decomposition Based Fuzzy Entropy and Support Vector Machine
Proceedings of the Sixth International Conference on Green and Human Information Technology, 2018
[14] Classification of EEG Signals Using Hybrid Feature Extraction and Ensemble Extreme Learning Machine
Neural Processing Letters, 2018
[15] Virtual Tai-Chi System: A smart-connected modality for rehabilitation
Smart Health, 2018
[16] Robust detection of epileptic seizures based on L1-penalized robust regression of EEG signals
Expert Systems with Applications, 2018
[17] Epileptic Seizure Detection: A Deep Learning Approach
2018
[18] Topolnogical classifier for detecting the emergence of epileptic seizures
2018
[19] Multiresolution analysis on nonlinear complexity measurement of EEG signal for epileptic discharge monitoring
2018
[20] A support vector machine approach for AF classification from a short single lead ECG recording
Physiological Measurement, 2018
[21] VLSI Design of SVM-Based Seizure Detection System With On-Chip Learning Capability
2018
[22] Epileptic Seizure Detection in Long-Term EEG Recordings by Using Wavelet-Based Directed Transfer Function
2018
[23] High performance EEG feature extraction for fast epileptic seizure detection
2017
[24] Developing enhanced classification methods for ECG and EEG signals
2017
[25] Correlated EEMD and Effective Feature Extraction for Both Periodic and Irregular Faults Diagnosis in Rotating Machinery
Energies, 2017
[26] Mouse epileptic seizure detection with multiple EEG features and simple thresholding technique
Journal of Neural Engineering, 2017
[27] The Feature Extraction Method of EEG Signals Based on Transition Network
Advances in Neural Networks - ISNN 2017, 2017
[28] The Feature Extraction Method of EEG Signals Based on the Loop Coefficient of Transition Network
Intelligent Computing Theories and Application, 2017
[29] The Potential Application of Multiscale Entropy Analysis of Electroencephalography in Children with Neurological and Neuropsychiatric Disorders.
Entropy, 2017
[30] Using EEG Data Analytics to Measure Meditation
Digital Human Modeling. Applications in Health, Safety, Ergonomics, and Risk Management: Health and Safety, 2017
[31] Electroencephalographic Signal Processing and Classification Techniques for Noninvasive Motor Imagery Based Brain Computer Interface
2017
[32] Application of Convex Optimization Techniques for Feature Extraction from EEG Signals
2017
[33] The potential application of multiscale entropy analysis of electroencephalography in children with neurological and neuropsychiatric disorders
Entropy, 2017
[34] Focal and Non-Focal EEG Signal Classification by Computing Area of 2D-PSR Obtained for IMF
2017
[35] A novel smoothness-based interpolation algorithm for division of focal plane Polarimeters
2017
[36] TEMPEST in USB
2017
[37] Automated diagnosis of Epilepsy from EEG signals using Ensemble Learning approach
Pattern Recognition Letters, 2017
[38] Altered resting-state EEG complexity in children with Tourette syndrome: A preliminary study.
Neuropsychology, 2017
[39] Multiple entropies performance measure for detection and localization of multi-channel epileptic EEG
Biomedical Signal Processing and Control, 2017
[40] Effects of force load, muscle fatigue and extremely low frequency magnetic stimulation on EEG signals during side arm lateral raise task
Physiological Measurement, 2017
[41] Automatic epileptic EEG detection using DT-CWT-based non-linear features
Biomedical Signal Processing and Control, 2017
[42] Application of empirical mode decomposition (EMD) for automated identification of congestive heart failure using heart rate signals
Neural Computing and Applications, 2016
[43] The distortion of data compression via compressed sensing in EEG telemonitoring for the epileptic
2016
[44] A quick approach to detect epilepsy and seizure in brain
International Journal of Advanced Intelligence Paradigms, 2016
[45] Topological classifier for detecting the emergence of epileptic seizures
2016
[46] Efficient feature extraction framework for EEG signals classification
2016
[47] 基于小波包节律和支持向量机的警戒低觉醒脑电信号识别方法
生物医学工程学杂志, 2016
[48] Time-Frequency Based Methods for Non-Stationary Signal Analysis with Application To EEG Signals
2016
[49] Principal dynamic mode analysis of neural mass model for the identification of epileptic states
AIP Conference Proceedings, 2016
[50] Automatic epilepsy detection using wavelet-based nonlinear analysis and optimized SVM
Biocybernetics and Biomedical Engineering, 2016
[51] Comprehensive Analysis of Extreme Learning Machine and Continuous Genetic Algorithm for Robust Classification of Epilepsy from EEG Signals
2016
[52] Medical Big Data: Neurological Diseases Diagnosis Through Medical Data Analysis
Data Science and Engineering, 2016
[53] Classifying Driving Fatigue Based on Combined Entropy Measure Using EEG Signals
2016
[54] Detection of epileptic seizure in EEG signals using linear least squares preprocessing
Computer Methods and Programs in Biomedicine, 2016
[55] The Diagnosis of Epilepsy by Gravitational Search Algorithm and Support Vector Machines
2016
[56] A Real Time EEG Analysis System
2016
[57] Research Article Automatic Epileptic Seizure Detection Using Scalp EEG and Advanced Artificial Intelligence Techniques
2015
[58] Application of entropies for automated diagnosis of epilepsy using EEG signals
Knowledge-Based Systems, 2015
[59] Classification of obsessive compulsive disorder by EEG complexity and hemispheric dependency measurements
International journal of neural systems, 2015
[60] Complexity of Multi-Channel Electroencephalogram Signal Analysis in Childhood Absence Epilepsy
PloS one, 2015
[61] Regularized online sequential extreme learning machine with adaptive regulation factor for time-varying nonlinear system
Neurocomputing, 2015
[62] Classification of ictal and seizure-free HRV signals with focus on lateralization of epilepsy
Technology and Health Care, 2015
[63] Application of entropies for automated diagnosis of epilepsy using EEG signals: A review
Knowledge-Based Systems, 2015
[64] Sparse Bayesian extreme learning committee machine for engine simultaneous fault diagnosis
Neurocomputing, 2015
[65] Classification of visually evoked potentials using extreme learning machine to command an intelligent robot chair with communication aid
Advanced Computing and Communication Systems, 2015 International Conference on, 2015
[66] Automated Detection of Central Apnea in Preterm Infants
2015
[67] Statistical Machine Learning in Brain State Classification using EEG Data
Open Journal of Big Data (OJBD), 2015
[68] Cultivating Chan with Calibration
International Journal of Reliable and Quality E-Healthcare (IJRQEH), 2015
[69] GMM better than SRC for classifying epilepsy risk levels from EEG signals
2015
[70] EEG signals classification based on wavelet packet and ensemble Extreme Learning Machine
2015
[71] Ensemble approach on enhanced compressed noise EEG data signal in wireless body area sensor network
2015
[72] Urgent Demand of the Continual Studies of Drug-Nutrition-Interrelation
Research Journal of Pharmaceutical, Biological and Chemical Sciences, 2015
[73] Automatic Epileptic Seizure Detection Using Scalp EEG and Advanced Artificial Intelligence Techniques
BioMed Research International, 2015
[74] Classifying Epileptic EEG Signals with Delay Permutation Entropy and Multi-scale K-Means
Signal and Image Analysis for Biomedical and Life Sciences, 2015
[75] Detection of Human Emotions Using Features Based on the Multiwavelet Transform of EEG Signals
Brain-Computer Interfaces, 2015
[76] A machine learning system for automated whole-brain seizure detection
Applied Computing and Informatics, 2015
[77] A Novel Feature Extraction Method for Epileptic EEG Based on Degree Distribution of Complex Network
2015
[78] Multi-scale sample entropy as a feature for working memory study
2014 7th Biomedical Engineering International Conference (BMEiCON), 2014
[79] Novel feature extraction method based on weight difference of weighted network for epileptic seizure detection
Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE, 2014
[80] Comparison of classification methods on EEG signals based on wavelet packet decomposition
Neural Computing and Applications, 2014
[81] Energy efficient telemonitoring of physiological signals via compressed sensing: A fast algorithm and power consumption evaluation
Biomedical Signal Processing and Control, 2014
[82] Linear and nonlinear analysis of normal and CAD-affected heart rate signals
Computer methods and programs in biomedicine, 2014
[83] Investigating the impacts of epilepsy on EEG-based person identification systems
Neural Networks (IJCNN), 2014 International Joint Conference on. IEEE, 2014
[84] Feature Extraction Method for Epileptic Seizure Detection Based on Cluster Coefficient Distribution of Complex Network
2014
[85] 基于递归量化分析与支持向量机的癫痫脑电自动检测方法
物理学报, 2014
[86] Automatic detection of epileptic EEG based on recurrence quantification analysis and SVM
2014
[87] Caracterización de medidas de regularidad en se?ales biomédicas. Robustez a outliers
2014
[88] Empirical Mode Decomposition Based Classification of Focal and Non-focal Seizure EEG Signals
Medical Biometrics (ICMB), 2014 International Conference on. IEEE, 2014
[89] Detection of Epileptic Seizure Event and Onset Using EEG
BioMed research international, 2014
[90] Design and Development of Prediction Model to Detect Seizure Activity Utilizing Higher Order Statistical Features of EEG signals
Research Journal of Pharmaceutical, Biological and Chemical Sciences, 2014
[91] The neoteric feature extraction method of epilepsy EEG based on the vertex strength distribution of weighted complex network
Neural Networks (IJCNN), 2014 International Joint Conference on. IEEE, 2014
[92] Multiscale sample entropy for time resolved epileptic seizure detection and fingerprinting
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on. IEEE, 2014
[93] ELM BASED DETECTION OF ABNORMALITY IN RETINAL IMAGE OF EYE DUE TO DIABETIC RETINOPATHY.
Journal of Theoretical and Applied Information Technology, 2014
[94] Epileptic seizure detection in EEGs signals using a fast weighted horizontal visibility algorithm
Computer methods and programs in biomedicine, 2014
[95] Using Shannon Entropy as EEG Signal Feature for Fast Person Identification
D Phung, D Tran, W Ma, P Nguyen, T Pham - elen.ucl.ac.be, 2014
[96] Performance Analysis of Extreme Learning Machine for Robust Classification of Epilepsy from EEG Signals
International Journal of Computer Applications, 2014
[97] A novel method for analysis of EEG background activity in epileptic patients and healthy subjects using Hilbert transform
International Journal of Biomedical Engineering and Technology, 2014
[98] Caracterización de medidas de regularidad en señales biomédicas. Robustez a outliers
2014
[99] Analysis of EEG signals using complex brain networks
2014
[100] Analysis of electroencephalogram background activity in epileptic patients and healthy subjects using dispersion entropy
Journal of Neuroscience and Neuroengineering, 2014
[101] Human seizure detection using quadratic Renyi entropy
2013
[102] Automatic Seizure Detection Using EEG
2013
[103] 西安交通大学学报 (未开通)
2013
[104] Detection of epileptic seizure in EEG recordings by spectral method and statistical analysis
Journal of Applied Sciences, 2013
[105] 脑卒中后抑郁症静息脑电信号非线性特征提取与分析
国际生物医学工程杂志 ISTIC?, 2013
[106] A novel approach for lie detection based on F-score and extreme learning machine
PloS one, 2013
[107] Unsupervised classification of epileptic EEG signals with multi scale K-means algorithm
Brain and Health Informatics, 2013
[108] Human seizure detection using quadratic Rényi entropy
Neural Engineering (NER), 2013 6th International IEEE/EMBS Conference on. IEEE, 2013
[109] Automatic Seizure Detection using Inter Quartile Range
International Journal of Computer Applications, 2012
[110] Epileptic seizure detection using wavelet transform based sample entropy and support vector machine
Information and Automation (ICIA), 2012 International Conference on. IEEE, 2012
[111] Multi-wavelet transform based epilepsy seizure detection
Biomedical Engineering and Sciences (IECBES), 2012 IEEE EMBS Conference on. IEEE, 2012
[112] 基于概率判决极端学习机的癫痫发作预报研究
中国生物医学工程学报, 2012
[113] Automated diagnosis of epileptic EEG using entropies
Biomedical Signal Processing and Control, 2012
[114] Application of non-linear and wavelet based features for the automated identification of epileptic EEG signals
International journal of neural systems, 2012
[115] Automatic epileptic seizure detection in EEGs based on optimized sample entropy and extreme learning machine
Journal of neuroscience methods, 2012
[116] Automated diagnosis of normal and alcoholic EEG signals
International journal of neural systems, 2012
[117] EEG signal classification using empirical mode decomposition and support vector machine
Proceedings of the International Conference on Soft Computing for Problem Solving (SocProS 2011) December 20-22, 2011. Springer India, 2012
[118] Epileptic EEG classification based on extreme learning machine and nonlinear features
Epilepsy research, 2011
[119] Methodology for epileptic episode detection using complexity-based features
New Challenges on Bioinspired Applications. Springer Berlin Heidelberg, 2011
[120] Automatic Seizure Detection Based on Wavelet-Chaos Methodology from EEG and its Sub-bands
A Abbaspour, A Kashaninia, M Amiri - khuisf.ac.ir, 2011
[121] Application of the Sample Entropy for Discrimination between Seizure and Seizure-Free EEG Signals.
IICAI, 2011
[122] Unsupervised Classification of Epileptic EEG Signals
2011