[1]
|
Research Review an Automatic Detection of Epilepsy in Human brain signal
|
|
International Journal of Advanced Computer Technology (IJACT)
NULL |
|
|
[2]
|
Automated identification of inter-ictal discharges using residual deep learning neural network amidst of various artefacts
|
|
Chaos, Solitons & Fractals,
2022 |
|
|
[3]
|
Surface electromyography classification using extreme learning machines and echo state networks
|
|
Research on Biomedical …,
2022 |
|
|
[4]
|
Machine Learning Characterization of Ictal and Interictal States in EEG Aimed at Automated Seizure Detection
|
|
Biomedicines,
2022 |
|
|
[5]
|
Automated epilepsy seizure detection from EEG signal based on hybrid CNN and LSTM model
|
|
Signal, Image and Video …,
2022 |
|
|
[6]
|
Epileptic seizure detection in EEG using mutual information-based best individual feature selection
|
|
Expert Systems with …,
2022 |
|
|
[7]
|
An Optimized Physical Reservoir Computing Through Genetic Algorithm
|
|
2022 12th …,
2022 |
|
|
[8]
|
Theoretical and methodological analysis of EEG based seizure detection and prediction: An exhaustive review
|
|
Journal of Neuroscience Methods,
2022 |
|
|
[9]
|
Improving aboveground biomass estimation of natural forests on the Tibetan Plateau using spaceborne LiDAR and machine learning algorithms
|
|
Ecological Indicators,
2022 |
|
|
[10]
|
Evaluation of classification approaches for distinguishing brain states predictive of episodic memory performance from electroencephalography: Abbreviated …
|
|
NeuroImage,
2022 |
|
|
[11]
|
Neuromorphic Architecture Accelerated Automated Seizure Detection in Multi-Channel Scalp EEG
|
|
Hameed, T John, Y Arjoune… - Sensors,
2022 |
|
|
[12]
|
Machine Learning Characterization of Ictal and Interictal States in EEG Aimed at Automated Seizure Detection. Biomedicines 2022, 10, 1491
|
|
2022 |
|
|
[13]
|
Aerodynamic system instability identification with sample entropy algorithm based on feature extraction
|
|
Propulsion and Power …,
2022 |
|
|
[14]
|
基于 EEG 的癫痫自动检测: 综述与展望
|
|
自动化学报,
2022 |
|
|
[15]
|
Détection automatique multi-échelle et de grande envergure d'oscillations intracérébrales pathologiques dans l'épilepsie par réseaux de neurones artificiels
|
|
2021 |
|
|
[16]
|
A method to denoise the epileptic EEG by EEMD and TFPF
|
|
2021 International Conference on Electronic …,
2021 |
|
|
[17]
|
Personalized EEG feature selection for low-complexity seizure monitoring
|
|
International Journal of …,
2021 |
|
|
[18]
|
A comparison study of polynomial-based PCA, KPCA, LDA and GDA feature extraction methods for epileptic and eye states EEG signals detection using …
|
|
Informatics in Medicine …,
2021 |
|
|
[19]
|
Epileptic seizure detection using STFT based peak mean feature and support vector machine
|
|
2021 8th International …,
2021 |
|
|
[20]
|
Seizure Detection Based on Adaptive Feature Extraction by Applying Extreme Learning Machines.
|
|
2021 |
|
|
[21]
|
Electroencephalography complexity in infantile spasms and its association with treatment response
|
|
2021 |
|
|
[22]
|
Data-driven methods for battery soh estimation: Survey and a critical analysis
|
|
IEEE Access,
2021 |
|
|
[23]
|
A novel automated seizure detection system from EMD-MSPCA denoised EEG: Refined composite multiscale sample, fuzzy and permutation entropies based scheme
|
|
2021 |
|
|
[24]
|
Automated detection of epileptic seizures using multiscale and refined composite multiscale dispersion entropy
|
|
2021 |
|
|
[25]
|
Automated Identification of Interictal Activity from EEG Signal Using Non-linear Features
|
|
2021 |
|
|
[26]
|
Classification of EEG signals for epileptic seizures detection and eye states identification using Jacobi polynomial transforms-based measures of complexity …
|
|
2021 |
|
|
[27]
|
Personalized EEG Feature Selection for Low-Complexity Seizure Monitoring.
|
|
2021 |
|
|
[28]
|
Identification of inter-ictal activity in novel data by bagged prediction method using beta and gamma waves
|
|
2021 |
|
|
[29]
|
Automatic detection of Epilepsy based on EMD-VMD feature components and ReliefF algorithm
|
|
2021 |
|
|
[30]
|
Investigating Various Approaches in Classification of EEG Signals Representing Distinct Cognitive States to Reach an Optimal Solution
|
|
2021 |
|
|
[31]
|
Accurate detection of myocardial infarction using non linear features with ECG signals
|
|
2021 |
|
|
[32]
|
Machine learning based novel cost-sensitive seizure detection classifier for imbalanced EEG data sets
|
|
2020 |
|
|
[33]
|
Comparison of Classification Models Using Entropy Based Features from Sub-bands of EEG.
|
|
2020 |
|
|
[34]
|
Analogy of Algorithms for Automatic Epileptic Seizure Detection
|
|
2020 |
|
|
[35]
|
Linear and nonlinear analyses of normal and fatigue heart rate variability signals for miners in high-altitude and cold areas
|
|
2020 |
|
|
[36]
|
XỬ LÝ ĐA KÊNH TÍN HIỆU ĐIỆN NÃO BẰNG PHƯƠNG PHÁP CỬA SỔ TRƯỢT ENTROPY ĐỂ XÁC ĐỊNH VỊ TRÍ VÙNG ĐỘNG KINH
|
|
2020 |
|
|
[37]
|
Dispersion Entropy for the automated detection of epileptic seizures
|
|
2020 |
|
|
[38]
|
Classification of autism spectrum disorder based on fluctuation entropy of spontaneous hemodynamic fluctuations
|
|
2020 |
|
|
[39]
|
Epileptic Seizure Detection using Bidimensional Empirical Mode Decomposition and Distance Metric Learning on Scalogram
|
|
2020 |
|
|
[40]
|
Smart Epilepsy Detection System Using Hybrid ANN‐PSO Network
|
|
2020 |
|
|
[41]
|
Statistical modeling and analysis of Internet latency traffic data
|
|
2020 |
|
|
[42]
|
Epilepsy Classification for Mining Deeper Relationships between EEG Channels based on GCN
|
|
2020 |
|
|
[43]
|
Feature Selection for Personalized EEG-Based Seizure Monitoring
|
|
2020 |
|
|
[44]
|
Swarm Intelligence Optimization: Algorithms and Applications
|
|
2020 |
|
|
[45]
|
Is EEG a Useful Examination Tool for Diagnosis of Epilepsy and Comorbid Psychiatric Disorders?
|
|
2020 |
|
|
[46]
|
Using Entropies for the Analysis of Brain Rhythms
|
|
International Journal of Signal Processing Systems,
2020 |
|
|
[47]
|
Automated Epilepsy Seizure Detection from EEG Signals Using Deep CNN Model
|
|
2020 |
|
|
[48]
|
Automatic Detection of Epileptic Spikes in Intracerebral EEG with Convolutional Kernel Density Estimation.
|
|
VISIGRAPP (2: HUCAPP),
2020 |
|
|
[49]
|
Machine Learning and EEG in Epilepsy
|
|
2020 |
|
|
[50]
|
Desarrollo de una metodología para la caracterización y clasificación de señales no estacionarias usando mediciones de entropía de permutación multiescalar
|
|
2020 |
|
|
[51]
|
Best Principal Submatrix Selection for the Maximum Entropy Sampling Problem: Scalable Algorithms and Performance Guarantees
|
|
2020 |
|
|
[52]
|
Approximation Algorithms for the Maximum Entropy Sampling Problem
|
|
2020 |
|
|
[53]
|
Multiband entropy-based feature-extraction method for automatic identification of epileptic focus based on high-frequency components in interictal iEEG
|
|
2020 |
|
|
[54]
|
Selection of features for patient-independent detection of seizure events using scalp EEG signals
|
|
2020 |
|
|
[55]
|
A review of epileptic seizure detection using machine learning classifiers
|
|
2020 |
|
|
[56]
|
Municipal Water Demand Forecasting in the Short and Long Term with ANN and SD Models
|
|
2020 |
|
|
[57]
|
Multiscale Distribution Entropy Analysis of Heart Rate Variability Using Differential Inter-Beat Intervals
|
|
2020 |
|
|
[58]
|
Algorithms for EEG-Based Monitoring of Epileptic Seizures
|
|
2020 |
|
|
[59]
|
A combination of statistical parameters for the detection of epilepsy and EEG classification using ANN and KNN classifier
|
|
2020 |
|
|
[60]
|
Attention Deficit Hyperactivity Disorder Diagnosis using non-linear univariate and multivariate EEG measurements: a preliminary study
|
|
2020 |
|
|
[61]
|
Visual seizure annotation and automated seizure detection using behind‐the‐ear electroencephalographic channels
|
|
2020 |
|
|
[62]
|
Feature Selection Using F-statistic Values for EEG Signal Analysis
|
|
2020 |
|
|
[63]
|
Development of a Unique Biometric-based Cryptographic Key Generation with Repeatability using Brain Signals
|
|
2020 |
|
|
[64]
|
Epilepsy Seizure Detection using Non-linear and DWT-based Features
|
|
2019 |
|
|
[65]
|
Discrete Wavelet Transform and Sample Entropy-Based EEG Dimensionality Reduction for Electroencephalogram classification
|
|
2019 |
|
|
[66]
|
Brain Tumor Localization and Segmentation Based on Pixel-Based Thresholding with Morphological Operation
|
|
2019 |
|
|
[67]
|
Application of Clustering Techniques on Statistical Features of EEG Signals for Seizure Detection
|
|
2019 |
|
|
[68]
|
Non Linear Analysis of the Effect of Stimulation on Epileptic Signals Generated at Right Hippocampus
|
|
2019 |
|
|
[69]
|
Automated Epileptic Seizure Detection Method Based on the Multi-attribute EEG Feature Pool and mRMR Feature Selection Method
|
|
2019 |
|
|
[70]
|
Entropy-based feature extraction technique in conjunction with wavelet packet transform for multi-mental task classification
|
|
2019 |
|
|
[71]
|
Formulation of a Novel Classification Indices for Classification of Human Hearing Abilities According to Cortical Auditory Event Potential signals
|
|
2019 |
|
|
[72]
|
Epileptic Seizure Detection and Classification Using Machine Learning
|
|
2019 |
|
|
[73]
|
EEG-based single-channel authentication systems with optimum electrode placement for different mental activities
|
|
2019 |
|
|
[74]
|
Visual seizure annotation and automated seizure detection using behind-the-ear EEG channels
|
|
2019 |
|
|
[75]
|
Automatic Detection of Epileptic Seizure Based on Approximate Entropy, Recurrence Quantification Analysis and Convolutional Neural Networks
|
|
2019 |
|
|
[76]
|
Machine Learning Methods for EEG-based Epileptic Seizure Detection
|
|
2019 |
|
|
[77]
|
Time-time analysis of electroencephalogram signals for epileptic seizure detection
|
|
2019 |
|
|
[78]
|
Using scalp EEG and intracranial EEG signals for predicting epileptic seizures: review of available methodologies
|
|
2019 |
|
|
[79]
|
Automatic Detection of Epileptic Spikes in Intracerebral EEG with Convolutional Kernel Density Estimation
|
|
4th International Conference on Human Computer Interaction Theory and Applications. SCITEPRESS-Science and Technology Publications,
2019 |
|
|
[80]
|
A novel automatic classification detection for epileptic seizure based on dictionary learning and sparse representation
|
|
2019 |
|
|
[81]
|
Epileptic Seizure detection with Permutation Fuzzy Entropy using robust machine learning techniques.
|
|
2019 |
|
|
[82]
|
Performance Analysis of Fuzzy Multilayer Support Vector Machine for Epileptic Seizure Disorder Classification using Auto Regression Features
|
|
2019 |
|
|
[83]
|
Application of Clustering Techniques on Statistical Features of EEG Signals for Seizure Detection.
|
|
2019 |
|
|
[84]
|
Classification of Hepatitis Viruses from Sequencing Chromatograms Using Multiscale Permutation Entropy and Support Vector Machines
|
|
2019 |
|
|
[85]
|
Unsupervised EEG feature extraction based on echo state network
|
|
Information Sciences,
2019 |
|
|
[86]
|
Optimized deep neural network architecture for robust detection of epileptic seizures using EEG signals
|
|
2019 |
|
|
[87]
|
Neural Network Based Brain Tumor Detection Using Wireless Infrared Imaging Sensor
|
|
2019 |
|
|
[88]
|
TỰ ĐỘNG PHÁT HIỆN CÁC CƠN ĐỘNG KINH BẰNG PHƯƠNG PHÁP CỬA SỔ TRƯỢT ENTROPY
|
|
Journal of Science and Technique,
2019 |
|
|
[89]
|
A new neural mass model driven method and its application in early epileptic seizure detection
|
|
2019 |
|
|
[90]
|
Auditory evoked potential in normal hearing and sensorineural hearing loss among Malay and Chinese adults/Ibrahim Amer Ibrahim
|
|
2019 |
|
|
[91]
|
Scalp and intracranial EEG quantitative analysis: robust detection and prediction of epileptic seizures
|
|
2019 |
|
|
[92]
|
Formulation of a Novel Classification Indices for Classification of Human Hearing Abilities According to Cortical Auditory Event Potential signals.
|
|
2019 |
|
|
[93]
|
Developing a Fair Physiological Signal Data Resource
|
|
2019 |
|
|
[94]
|
Brain data mining for epileptic seizure‑detection
|
|
2018 |
|
|
[95]
|
A support vector machine approach for AF classification from a short single-lead ECG recording
|
|
2018 |
|
|
[96]
|
Imbalance Learning Using Neural Networks for Seizure Detection
|
|
2018 |
|
|
[97]
|
Robust Detection of Epileptic Seizures Using Deep Neural Networks
|
|
2018 |
|
|
[98]
|
Brain Data Mining for Epileptic Seizure-Detection
|
|
2018 |
|
|
[99]
|
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 |
|
|
[100]
|
Classification of EEG Signals Using Hybrid Feature Extraction and Ensemble Extreme Learning Machine
|
|
Neural Processing Letters,
2018 |
|
|
[101]
|
Virtual Tai-Chi System: A smart-connected modality for rehabilitation
|
|
Smart Health,
2018 |
|
|
[102]
|
Robust detection of epileptic seizures based on L1-penalized robust regression of EEG signals
|
|
Expert Systems with Applications,
2018 |
|
|
[103]
|
Epileptic Seizure Detection: A Deep Learning Approach
|
|
2018 |
|
|
[104]
|
Topolnogical classifier for detecting the emergence of epileptic seizures
|
|
2018 |
|
|
[105]
|
Multiresolution analysis on nonlinear complexity measurement of EEG signal for epileptic discharge monitoring
|
|
2018 |
|
|
[106]
|
A support vector machine approach for AF classification from a short single lead ECG recording
|
|
Physiological Measurement,
2018 |
|
|
[107]
|
VLSI Design of SVM-Based Seizure Detection System With On-Chip Learning Capability
|
|
2018 |
|
|
[108]
|
Epileptic Seizure Detection in Long-Term EEG Recordings by Using Wavelet-Based Directed Transfer Function
|
|
2018 |
|
|
[109]
|
LEARNING TO MODEL A MEDITATION BRAIN STATE USING EEG DATA
|
|
2018 |
|
|
[110]
|
EEG Classification in Brain Computer Interface (BCI): A Pragmatic Appraisal
|
|
2018 |
|
|
[111]
|
TEMPEST in USB
|
|
2017 |
|
|
[112]
|
Analysis of PAC Learning Based Bayesian Optimization with Autoencoders for Epilepsy Classification from EEG Signals
|
|
2017 |
|
|
[113]
|
GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES
|
|
2017 |
|
|
[114]
|
Hyperspectral image band selection via global optimal clustering
|
|
2017 |
|
|
[115]
|
High performance EEG feature extraction for fast epileptic seizure detection
|
|
2017 |
|
|
[116]
|
Developing enhanced classification methods for ECG and EEG signals
|
|
2017 |
|
|
[117]
|
Correlated EEMD and Effective Feature Extraction for Both Periodic and Irregular Faults Diagnosis in Rotating Machinery
|
|
Energies,
2017 |
|
|
[118]
|
Mouse epileptic seizure detection with multiple EEG features and simple thresholding technique
|
|
Journal of Neural Engineering,
2017 |
|
|
[119]
|
The Feature Extraction Method of EEG Signals Based on Transition Network
|
|
Advances in Neural Networks - ISNN 2017,
2017 |
|
|
[120]
|
The Feature Extraction Method of EEG Signals Based on the Loop Coefficient of Transition Network
|
|
Intelligent Computing Theories and Application,
2017 |
|
|
[121]
|
The Potential Application of Multiscale Entropy Analysis of Electroencephalography in Children with Neurological and Neuropsychiatric Disorders.
|
|
Entropy,
2017 |
|
|
[122]
|
Using EEG Data Analytics to Measure Meditation
|
|
Digital Human Modeling. Applications in Health, Safety, Ergonomics, and Risk Management: Health and Safety,
2017 |
|
|
[123]
|
Electroencephalographic Signal Processing and Classification Techniques for Noninvasive Motor Imagery Based Brain Computer Interface
|
|
2017 |
|
|
[124]
|
Application of Convex Optimization Techniques for Feature Extraction from EEG Signals
|
|
2017 |
|
|
[125]
|
The potential application of multiscale entropy analysis of electroencephalography in children with neurological and neuropsychiatric disorders
|
|
Entropy,
2017 |
|
|
[126]
|
Focal and Non-Focal EEG Signal Classification by Computing Area of 2D-PSR Obtained for IMF
|
|
2017 |
|
|
[127]
|
A novel smoothness-based interpolation algorithm for division of focal plane Polarimeters
|
|
2017 |
|
|
[128]
|
Automated diagnosis of Epilepsy from EEG signals using Ensemble Learning approach
|
|
Pattern Recognition Letters,
2017 |
|
|
[129]
|
Altered resting-state EEG complexity in children with Tourette syndrome: A preliminary study.
|
|
Neuropsychology,
2017 |
|
|
[130]
|
Multiple entropies performance measure for detection and localization of multi-channel epileptic EEG
|
|
Biomedical Signal Processing and Control,
2017 |
|
|
[131]
|
Effects of force load, muscle fatigue and extremely low frequency magnetic stimulation on EEG signals during side arm lateral raise task
|
|
Physiological Measurement,
2017 |
|
|
[132]
|
Automatic epileptic EEG detection using DT-CWT-based non-linear features
|
|
Biomedical Signal Processing and Control,
2017 |
|
|
[133]
|
Application of empirical mode decomposition (EMD) for automated identification of congestive heart failure using heart rate signals
|
|
Neural Computing and Applications,
2016 |
|
|
[134]
|
The distortion of data compression via compressed sensing in EEG telemonitoring for the epileptic
|
|
2016 |
|
|
[135]
|
A quick approach to detect epilepsy and seizure in brain
|
|
International Journal of Advanced Intelligence Paradigms,
2016 |
|
|
[136]
|
Topological classifier for detecting the emergence of epileptic seizures
|
|
2016 |
|
|
[137]
|
Efficient feature extraction framework for EEG signals classification
|
|
2016 |
|
|
[138]
|
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 |
|
|
[139]
|
Time-Frequency Based Methods for Non-Stationary Signal Analysis with Application To EEG Signals
|
|
2016 |
|
|
[140]
|
Principal dynamic mode analysis of neural mass model for the identification of epileptic states
|
|
AIP Conference Proceedings,
2016 |
|
|
[141]
|
Automatic epilepsy detection using wavelet-based nonlinear analysis and optimized SVM
|
|
Biocybernetics and Biomedical Engineering,
2016 |
|
|
[142]
|
Comprehensive Analysis of Extreme Learning Machine and Continuous Genetic Algorithm for Robust Classification of Epilepsy from EEG Signals
|
|
2016 |
|
|
[143]
|
Medical Big Data: Neurological Diseases Diagnosis Through Medical Data Analysis
|
|
Data Science and Engineering,
2016 |
|
|
[144]
|
Classifying Driving Fatigue Based on Combined Entropy Measure Using EEG Signals
|
|
2016 |
|
|
[145]
|
Detection of epileptic seizure in EEG signals using linear least squares preprocessing
|
|
Computer Methods and Programs in Biomedicine,
2016 |
|
|
[146]
|
The Diagnosis of Epilepsy by Gravitational Search Algorithm and Support Vector Machines
|
|
2016 |
|
|
[147]
|
A Real Time EEG Analysis System
|
|
2016 |
|
|
[148]
|
Time-frequency based methods for nonstationary signal analysis with application to EEG signals
|
|
2016 |
|
|
[149]
|
Entropy Feature Extraction of EEG Signals for Automatic Person Identification
|
|
2016 |
|
|
[150]
|
Research Article Automatic Epileptic Seizure Detection Using Scalp EEG and Advanced Artificial Intelligence Techniques
|
|
2015 |
|
|
[151]
|
Application of entropies for automated diagnosis of epilepsy using EEG signals
|
|
Knowledge-Based Systems,
2015 |
|
|
[152]
|
Classification of obsessive compulsive disorder by EEG complexity and hemispheric dependency measurements
|
|
International journal of neural systems,
2015 |
|
|
[153]
|
Complexity of Multi-Channel Electroencephalogram Signal Analysis in Childhood Absence Epilepsy
|
|
PloS one,
2015 |
|
|
[154]
|
Regularized online sequential extreme learning machine with adaptive regulation factor for time-varying nonlinear system
|
|
Neurocomputing,
2015 |
|
|
[155]
|
Classification of ictal and seizure-free HRV signals with focus on lateralization of epilepsy
|
|
Technology and Health Care,
2015 |
|
|
[156]
|
Application of entropies for automated diagnosis of epilepsy using EEG signals: A review
|
|
Knowledge-Based Systems,
2015 |
|
|
[157]
|
Sparse Bayesian extreme learning committee machine for engine simultaneous fault diagnosis
|
|
Neurocomputing,
2015 |
|
|
[158]
|
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 |
|
|
[159]
|
Automated Detection of Central Apnea in Preterm Infants
|
|
2015 |
|
|
[160]
|
Statistical Machine Learning in Brain State Classification using EEG Data
|
|
Open Journal of Big Data (OJBD),
2015 |
|
|
[161]
|
Cultivating Chan with Calibration
|
|
International Journal of Reliable and Quality E-Healthcare (IJRQEH),
2015 |
|
|
[162]
|
GMM better than SRC for classifying epilepsy risk levels from EEG signals
|
|
2015 |
|
|
[163]
|
EEG signals classification based on wavelet packet and ensemble Extreme Learning Machine
|
|
2015 |
|
|
[164]
|
Ensemble approach on enhanced compressed noise EEG data signal in wireless body area sensor network
|
|
2015 |
|
|
[165]
|
Urgent Demand of the Continual Studies of Drug-Nutrition-Interrelation
|
|
Research Journal of Pharmaceutical, Biological and Chemical Sciences,
2015 |
|
|
[166]
|
Automatic Epileptic Seizure Detection Using Scalp EEG and Advanced Artificial Intelligence Techniques
|
|
BioMed Research International,
2015 |
|
|
[167]
|
Classifying Epileptic EEG Signals with Delay Permutation Entropy and Multi-scale K-Means
|
|
Signal and Image Analysis for Biomedical and Life Sciences,
2015 |
|
|
[168]
|
Detection of Human Emotions Using Features Based on the Multiwavelet Transform of EEG Signals
|
|
Brain-Computer Interfaces,
2015 |
|
|
[169]
|
A machine learning system for automated whole-brain seizure detection
|
|
Applied Computing and Informatics,
2015 |
|
|
[170]
|
A Novel Feature Extraction Method for Epileptic EEG Based on Degree Distribution of Complex Network
|
|
2015 |
|
|
[171]
|
Multi-scale sample entropy as a feature for working memory study
|
|
2014 7th Biomedical Engineering International Conference (BMEiCON),
2014 |
|
|
[172]
|
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 |
|
|
[173]
|
Comparison of classification methods on EEG signals based on wavelet packet decomposition
|
|
Neural Computing and Applications,
2014 |
|
|
[174]
|
Energy efficient telemonitoring of physiological signals via compressed sensing: A fast algorithm and power consumption evaluation
|
|
Biomedical Signal Processing and Control,
2014 |
|
|
[175]
|
Linear and nonlinear analysis of normal and CAD-affected heart rate signals
|
|
Computer methods and programs in biomedicine,
2014 |
|
|
[176]
|
Investigating the impacts of epilepsy on EEG-based person identification systems
|
|
Neural Networks (IJCNN), 2014 International Joint Conference on. IEEE,
2014 |
|
|
[177]
|
Feature Extraction Method for Epileptic Seizure Detection Based on Cluster Coefficient Distribution of Complex Network
|
|
NULL
2014 |
|
|
[178]
|
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 |
|
|
[179]
|
Automatic detection of epileptic EEG based on recurrence quantification analysis and SVM
|
|
NULL
2014 |
|
|
[180]
|
Caracterización de medidas de regularidad en se?ales biomédicas. Robustez a outliers
|
|
NULL
2014 |
|
|
[181]
|
Empirical Mode Decomposition Based Classification of Focal and Non-focal Seizure EEG Signals
|
|
Medical Biometrics (ICMB), 2014 International Conference on. IEEE,
2014 |
|
|
[182]
|
Detection of Epileptic Seizure Event and Onset Using EEG
|
|
BioMed research international,
2014 |
|
|
[183]
|
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 |
|
|
[184]
|
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 |
|
|
[185]
|
Multiscale sample entropy for time resolved epileptic seizure detection and fingerprinting
|
|
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on. IEEE,
2014 |
|
|
[186]
|
ELM BASED DETECTION OF ABNORMALITY IN RETINAL IMAGE OF EYE DUE TO DIABETIC RETINOPATHY.
|
|
Journal of Theoretical and Applied Information Technology,
2014 |
|
|
[187]
|
Epileptic seizure detection in EEGs signals using a fast weighted horizontal visibility algorithm
|
|
Computer methods and programs in biomedicine,
2014 |
|
|
[188]
|
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 |
|
|
[189]
|
Performance Analysis of Extreme Learning Machine for Robust Classification of Epilepsy from EEG Signals
|
|
International Journal of Computer Applications,
2014 |
|
|
[190]
|
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 |
|
|
[191]
|
Caracterización de medidas de regularidad en señales biomédicas. Robustez a outliers
|
|
2014 |
|
|
[192]
|
Analysis of EEG signals using complex brain networks
|
|
2014 |
|
|
[193]
|
Analysis of electroencephalogram background activity in epileptic patients and healthy subjects using dispersion entropy
|
|
Journal of Neuroscience and Neuroengineering,
2014 |
|
|
[194]
|
Research Article Detection of Epileptic Seizure Event and Onset Using EEG
|
|
2014 |
|
|
[195]
|
Human seizure detection using quadratic Renyi entropy
|
|
2013 |
|
|
[196]
|
Automatic Seizure Detection Using EEG
|
|
2013 |
|
|
[197]
|
西安交通大学学报 (未开通)
|
|
2013 |
|
|
[198]
|
Detection of epileptic seizure in EEG recordings by spectral method and statistical analysis
|
|
Journal of Applied Sciences,
2013 |
|
|
[199]
|
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 |
|
|
[200]
|
A novel approach for lie detection based on F-score and extreme learning machine
|
|
PloS one,
2013 |
|
|
[201]
|
Unsupervised classification of epileptic EEG signals with multi scale K-means algorithm
|
|
Brain and Health Informatics,
2013 |
|
|
[202]
|
Human seizure detection using quadratic Rényi entropy
|
|
Neural Engineering (NER), 2013 6th International IEEE/EMBS Conference on. IEEE,
2013 |
|
|
[203]
|
Automatic Seizure Detection using Inter Quartile Range
|
|
International Journal of Computer Applications,
2012 |
|
|
[204]
|
Epileptic seizure detection using wavelet transform based sample entropy and support vector machine
|
|
Information and Automation (ICIA), 2012 International Conference on. IEEE,
2012 |
|
|
[205]
|
Multi-wavelet transform based epilepsy seizure detection
|
|
Biomedical Engineering and Sciences (IECBES), 2012 IEEE EMBS Conference on. IEEE,
2012 |
|
|
[206]
|
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 |
|
|
[207]
|
Automated diagnosis of epileptic EEG using entropies
|
|
Biomedical Signal Processing and Control,
2012 |
|
|
[208]
|
Application of non-linear and wavelet based features for the automated identification of epileptic EEG signals
|
|
International journal of neural systems,
2012 |
|
|
[209]
|
Automatic epileptic seizure detection in EEGs based on optimized sample entropy and extreme learning machine
|
|
Journal of neuroscience methods,
2012 |
|
|
[210]
|
Automated diagnosis of normal and alcoholic EEG signals
|
|
International journal of neural systems,
2012 |
|
|
[211]
|
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 |
|
|
[212]
|
基于回声状态网络的脑电信号特征提取
|
|
2012 |
|
|
[213]
|
Monocular camera trajectory optimization using LiDAR data
|
|
2011 |
|
|
[214]
|
Epileptic EEG classification based on extreme learning machine and nonlinear features
|
|
Epilepsy research,
2011 |
|
|
[215]
|
Methodology for epileptic episode detection using complexity-based features
|
|
New Challenges on Bioinspired Applications. Springer Berlin Heidelberg,
2011 |
|
|
[216]
|
Automatic Seizure Detection Based on Wavelet-Chaos Methodology from EEG and its Sub-bands
|
|
A Abbaspour, A Kashaninia, M Amiri - khuisf.ac.ir,
2011 |
|
|
[217]
|
Application of the Sample Entropy for Discrimination between Seizure and Seizure-Free EEG Signals.
|
|
IICAI,
2011 |
|
|
[218]
|
Unsupervised Classification of Epileptic EEG Signals
|
|
2011 |
|
|
[219]
|
Comparison of Classification Models Using Entropy Based Features from Sub-bands of EEG Comparison of Classification Models Using Entropy Based …
|
|
|
|
|
[220]
|
Seizure Detection Based on Adaptive Feature Extraction by Applying Extreme Learning Machines Seizure Detection Based on Adaptive Feature …
|
|
M Baykara
|
|
|
[221]
|
Brain damage detection using machine learning approach
|
|
|
|
|
[222]
|
U Rajendra Acharya1, 2, 3, Hamido Fujita4, Vidya K Sudarshan1*, Oh Shu Lih1, Muhammad Adam1, Joel EW Koh1, Tan Jen Hong1, Chua K Chua1 …
|
|
|
|
|
[223]
|
PHÂN TÍCH TÍN HIỆU ĐIỆN NÃO BẰNG PHƯƠNG PHÁP CỬA SỔ TRƯỢT ENTROPY MẪU (SAMPLE ENTROPY) HỖ TRỢ PHÁT HIỆN BỆNH ĐỘNG KINH
|
|
|
|
|