Pattern Recognition of Motor Imagery EEG using Wavelet Transform

Journals Menu

Follow SCIRP

	+1 323-425-8868
	customer@scirp.org
	+86 18163351462(WhatsApp)
	1655362766

	Paper Publishing WeChat

Journal of Biomedical Science and Engineering

ISSN Print: 1937-6871
ISSN Online: 1937-688X
www.scirp.org/journal/jbise
E-mail: jbise@scirp.org

Google-based Impact Factor: 0.66
Citations h5-index & Ranking

Journals Menu

"Pattern Recognition of Motor Imagery EEG using Wavelet Transform"
written by Baoguo Xu, Aiguo Song,
published by Journal of Biomedical Science and Engineering, Vol.1 No.1, 2008

has been cited by the following article(s):

Google Scholar
CrossRef

[1]	Motor imagery EEG signal classification using long short-term memory deep network and neighbourhood component analysis
	International Journal of Information Technology, 2022

[2]	Pre-processing and feature extraction
	García, O Mendoza-Montoya… - … and Classification Using …, 2022

[3]	An approach to EEG based BCI for motor imagery using time-frequency representation and CNN
	2022 29th International Conference on …, 2022

[4]	A CNN Approach for Bidirectional Brainwave Controller for Intelligent Vehicles
	Human Factors in Intelligent Vehicles, 2022

[5]	Deep neural network with harmony search based optimal feature selection of EEG signals for motor imagery classification
	International Journal of Information Technology, 2022

[6]	A multiwavelet-based sparse time-varying autoregressive modeling for motor imagery EEG classification
	Computers in Biology and Medicine, 2022

[7]	A New PLV-Spatial Filtering to Improve the Classification Performance in BCI Systems
	Chinea, JF Gómez-González… - IEEE Transactions on …, 2022

[8]	ConTraNet: A single end-to-end hybrid network for EEG-based and EMG-based human machine interfaces
	ur-Rehman, T Glasmachers… - arXiv preprint arXiv …, 2022

[9]	Manual 3D Control of an Assistive Robotic Manipulator Using Alpha Rhythms and an Auditory Menu: A Proof-of-Concept
	Signals, 2022

[10]	Machine Learning Applications to Brain Computer Interfaces
	2021

[11]	Brain-computer interface: Advancement and challenges
	Sensors, 2021

[12]	Motor Imagery: A review of existing techniques, challenges and potentials
	2021 IEEE 45th …, 2021

[13]	Analysis of EEG-Based Stroke Severity Groups Clustering using K-Means
	… Technology and Its …, 2021

[14]	EEG Signal Analysis Based Brain-Computer
	Menoufia Journal of …, 2021

[15]	Fuzzy support vector machine with joint optimization of genetic algorithm and fuzzy c-means
	Technology and Health Care, 2021

[16]	Optimum Order Selection Criterion for Autoregressive Models of Bandlimited EEG Signals
	2021

[17]	Reducing Sensors in Mental Imagery Based Cognitive Task for Brain Computer Interface
	2020

[18]	An Improved Composite Multiscale Fuzzy Entropy for Feature Extraction of MI-EEG
	2020

[19]	Analysis of the EEG rhythms based on the Empirical Mode Decomposition during motor imagery when using a lower-limb exoskeleton. A case of study
	2020

[20]	Versatile Brain-Computer-Interface for Severely-Disabled People
	2020

[21]	Analysis of the EEG rhythms based on the empirical mode decomposition during motor imagery when using a lower-limb exoskeleton. A case study
	Vidal… - Frontiers in …, 2020

[22]	YAPAY SİNİR AĞLARI KULLANILARAK İMLEÇ YÖNÜ TESPİTİ
	2020

[23]	Statistical Analysis of Subject-Specific EEG data during Stroke Rehabilitation Monitoring
	2020

[24]	Statistical Analysis for EEG Patterns Comparison Between Real Motion and Imagery Motion
	2020

[25]	Introduction to Motor Imagery-Based Brain-Computer Interface: Time, Frequency, and Phase Analysis-Based Feature Extraction for Two Class MI Classification
	2020

[26]	Amplitude Modulation Index as Feature in a Brain Computer Interface Amplitude Modulation Index as Feature in a Brain Computer Interface
	Traitement du Signal, 2019

[27]	Filtering techniques for channel selection in motor imagery EEG applications: a survey
	2019

[28]	Ongoing temporal dynamics of broadband EEG during movement intention for BCI
	2019

[29]	Fuzzy entropy for Feature optimization In Motor Imagery based Brain Computer Interface
	2019

[30]	Evaluation of quantitative and qualitative features for the acoustic analysis of domestic dogs' vocalizations
	2019

[31]	Study of Feature Extraction Methods for BCI Applications
	2019

[32]	Desıgn of Brain-Computer Interface for Controlling A Virtual Keyboard
	2019

[33]	Classification of Motor Imagery Tasks using Phase Space Reconstruction and Empirical Mode Decomposition
	2019

[34]	Sanal Klavye Kontrolü İçin Beyin-Bilgisayar Arayüzü Tasarımı Desıgn of Brain-Computer Interface for Controlling A Virtual Keyboard
	Conference Paper, 2019

[35]	Sanal Klavye Kontrolü İçin Beyin-Bilgisayar Arayüzü Tasarımı Design of Brain-Computer Interface for Controlling A Virtual Keyboard
	2019

[36]	Wavelet transform based approach for EEG feature selection of motor imagery data for braincomputer interfaces
	2019

[37]	Identifying EEG Parameters to Monitor Stroke Rehabilitation using Individual Analysis
	2019

[38]	Classification of Motor Imagery Activities Using Band Power and Second Order Difference Plot
	2019

[39]	Amplitude Modulation Index as Feature in a Brain Computer Interface
	2019

[40]	Combined CNN and LSTM for Motor Imagery Classification
	2019

[41]	RECURRENCE PLOT STRUCTURES REFLECT MOTOR-RELATED EEG PATTERN
	2019

[42]	Hardware-Software Complex of the Mobile Brain-Computer Interface for Technical Means of Rehabilitation
	2019

[43]	РАЗРАБОТКА МЕТОДОВ И АЛГОРИТМОВ ДЛЯ КЛАССИФИКАЦИИ МНОГОМЕРНЫХ ВРЕМЕННЫХ РЯДОВ В ИНТЕРФЕЙСЕ МОЗГ-КОМПЬЮТЕР
	2019

[44]	АДАПТИВНЫЙ СЕНСОМОТОРНЫЙ ИНТЕРФЕЙС «МОЗГ-КОМПЬЮТЕР» ДЛЯ УПРАВЛЕНИЯ СРЕДСТВАМИ РЕАБИЛИТАЦИИ
	2019

[45]	Amplitude Modulation Index as Feature in a Brain Computer Interface.
	2019

[46]	Pengembangan Sistem Kendali Tangan Prostetik Berbasis Electroencephalogram (EEG) bagi Penderita Cacat Amputasi
	2018

[47]	Determination of 1 DOF Elbow Angles by Using EEG Signals
	2018

[48]	Evolutionary Wavelet Neural Networks in Data Classification and Dynamic Control
	2018

[49]	An Experimental Analysis of Motor Imagery EEG Signals Using Feature Extraction and Classification Methodologies
	2018

[50]	Classification of Motor Imagery Tasks Using Inter Trial Variance In The Brain Computer Interface
	2018

[51]	Brain Computer Interface Untuk Menggerakkan Animator Pemukul Bass Drum Menggunakan Wavelet dan Support Vector Machine
	2018

[52]	Procesamiento de señales electroencefalográficas para conversión a palabras
	2018

[53]	Gaze controlled prosthetic arm with EMG and EEG input interface
	2017

[54]	Towards sign language recognition using EEG-based motor imagery brain computer interface
	2017

[55]	Research and development of methods and means, based on the analysis of processes of human brain activity, for creating the control systems of the …
	EMBEC & NBC 2017, 2017

[56]	Cost-efficient brainwave controller for automated vehicles route decisions
	2017

[57]	Evolving multi-dimensional wavelet neural networks for classification using Cartesian Genetic Programming
	Neurocomputing, 2017

[58]	Progress in EEG-Based Brain Robot Interaction Systems
	Computational Intelligence and Neuroscience, 2017

[59]	Research and development of methods and means, based on the analysis of processes of human brain activity, for creating the control systems of the …
	EMBEC & NBC 2017, 2017

[60]	Multiple Classifier System for Motor Imagery Task Classification
	2017

[61]	Caracterización y clasificación de señales eléctricas cerebrales para aplicaciones BCI (Interfaz Cerebro Computador).
	2017

[62]	Brainwave Controller Development for Intelligent Vehicle
	2017

[63]	Plataforma para análise do sinal de EEG aplicado ao ERD/ERS no reconhecimento em tempo real da imaginação do movimento
	2017

[64]	Design and development of EEG controlled mobile robots
	2016

[65]	Brain-Computer Interface controlled functional electrical stimulation system for paralyzed arm
	2016

[66]	Classification of motor imagery movements using multivariate empirical mode decomposition and short time Fourier transform based hybrid method
	Engineering Science and Technology, an International Journal, 2016

[67]	An Overview of Controlling Vehicle Direction Using Brain Rhythms
	International Journal of Science and Research, 2016

[68]	Mixture of autoregressive modeling orders and its implication on single trial EEG classification
	Expert Systems with Applications, 2016

[69]	Classification of EEG Signals for Motor Imagery based on Mutual Information and Adaptive Neuro Fuzzy Inference System
	International Journal of System Dynamics Applications (IJSDA), 2016

[70]	Influences of the signal border extension in the discrete wavelet transform in EEG spike detection
	2016

[71]	POST STROKE REHABILITATION USING BRAIN-COMPUTER INTERFACE AND MOTOR IMAGERY
	International Journal of Modern Trends in Engineering and Science, 2016

[72]	Evaluation of local field potential signals in decoding of visual attention
	Cognitive Neurodynamics, 2015

[73]	Diseño Y Construcción De Un Prototipo De Interfaz Cerebro-Computadora (ICC) Para El Control De Un Puntero Indicador
	2015

[74]	Multiscale AM-FM methods on EEG signals for motor task classification
	Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE, 2015

[75]	Using novel stimuli and alternative signal processing techniques to enhance BCI paradigms
	2015

[76]	A feature extraction method based on dictionary learning for EEG
	Natural Computation (ICNC), 2015 11th International Conference on, 2015

[77]	Выбор оптимальных частотных диапазонов сигнала электроэнцефалограммы в интерфейсе мозг-компьютер
	НАУКА И ОБРАЗОВАНИЕ: ЭЛЕКТРОННОЕ НАУЧНО-ТЕХНИЧЕСКОЕ ИЗДАНИЕ, 2015

[78]	Robotic Neurorehabilitation System Design for Stroke Patients
	School of Instrument Science and Engineering, Southeast University, Nanjing , 2015

[79]	Выделение характерных признаков сигнала электроэнцефалограммы с помощью анализа энтропии
	Наука и Образование. МГТУ им. Н.Э. Баумана., 2014

[80]	EEG TABANLI BEYİN-BİLGİSAYAR ARAYÜZÜ SİSTEMLERİNDE ÖZNİTELİK ÇIKARMA YÖNTEMLERİ
	Journal of Engineering Sciences and Design, 2014

[81]	Обзор методов обработки сигнала электроэнцефалограммы в интерфейсах мозг-компьютер
	2014

[82]	EMD 를 이용한 EEG 기반 움직임 상상 분류
	HCI 2014, 2014

[83]	Classifications of motor imagery tasks using k-nearest neighbors
	Neural Network Applications in Electrical Engineering (NEUREL), 2014 12th Symposium on, 2014

[84]	EEG-based motor imagery analysis using empirical mode decomposition
	HCI 2014, 2014

[85]	Россия, МГТУ им. НЭ Баумана
	2014

[86]	Sub-band-power-based efficient Brain Computer Interface for wheelchair control
	Computer Applications & Research (WSCAR), 2014 World Symposium on. IEEE, 2014., 2014

[87]	Classifications of Motor Imagery Tasks in Brain Computer Interface Using Linear Discriminant Analysis
	International Journal of Advanced Research in Artificial Intelligence (IJARAI), 2014

[88]	Application of Signal Processing and Pattern Recognition By Wavelet Transform
	SE Razavi, M Bahadorzade, H Bolandpour - researchgate.net, 2014

[89]	Motor Imagery EEG Classification Method using EMD and FFT
	????????, 2014

[90]	Entropy Analysis as an Electroencephalogram Feature Extraction Method.
	Science & Education of Bauman MSTU/Nauka i Obrazovanie of Bauman MSTU, 2014

[91]	Novel use of Empirical Mode Decomposition in single-trial classification of motor imagery for use in brain-computer interfaces
	Novel use of Empirical Mode Decomposition in single-trial classification of motor imagery for use in brain-computer interfaces, 2013

[92]	Multiresolution analysis over simple graphs for brain computer interfaces
	Journal of neural engineering, 2013

[93]	EEG Motor Imagery Classification of Upper Limb Movements.
	BIOSIGNALS, 2013

[94]	Spektrum Frekuensi Sinyal EEG Terhadap Pergerakan Motorik dan Imajinasi Pergerakan Motorik
	2013

[95]	Rancangan Perumahan dan Interaksi Penghuni dengan Sekitar Studi Kasus: Perumahan Menengah Atas di Yogyakarta
	2013

[96]	Применение имитационного моделирования для контроля вычислительных систем гидролокационных комплексов
	2013

[97]	Multiresolution analysisover simple graphs for brain computer interfaces
	Journal of Neural Engineering, 2013

[98]	АНАЛИЗ И ИДЕНТИФИКАЦИЯ ПРОЦЕССОВ ДЕЯТЕЛЬНОСТИ ГОЛОВНОГО МОЗГА ЧЕЛОВЕКА В ЦЕЛЯХ ИССЛЕДОВАНИЯ И РАЗРАБОТКИ МЕТОДА УПРАВЛЕНИЯ АНТРОПОМОРФНЫМ ТЕХНИЧЕСКИМ УСТРОЙСТВОМ
	2013

[99]	Spectral analysis of EEG signals generated from imagined writing
	2012

[100]	Multi-objective metaheuristics for preprocessing EEG data in brain–computer interfaces
	Engineering Optimization, 2012

[101]	A BCI motor imagery experiment based on parametric feature extraction and fisher criterion
	Electrical Communications and Computers (CONIELECOMP), 2012 22nd International Conference on. IEEE, 2012., 2012

[102]	Wavelet Design by Means of Multi-Objective GAs for Motor Imagery EEG Analysis
	J Asensio, E Galvan, R Palaniappan, JQ Gan - scss.tcd.ie, 2011

[103]	Signal Processing and Pattern Recognition Using Wavelet Transform
	International Journal of Science and Advanced Technology, 2011

[104]	Obrada elektroencefalografskog signala u svrhu ostvarivanja su?elja mozak-ra?unalo
	AB ?efer - bme.unizg.hr, 2011

[105]	Clasificación de palabras no pronunciadas presentes en Electroencefalogramas (EEG)
	García, Alejandro Antonio Torres, Carlos Alberto Reyes García, Luis Villase?or Pineda, Luis Enrique Erro, and Sta Ma Tonantzintla, 2011

[106]	Tensor scheme using GTDA for EEG mental task classification
	Proceedings of the 10th WSEAS international conference on Wavelet analysis and multirate systems. World Scientific and Engineering Academy and Society (WSEAS), 2010., 2010

[107]	Design of a brain computer interface system based on electroencephalogram (EEG)
	Education and Research Conference (EDERC), 2010 4th European. IEEE, 2010., 2010

[108]	Controlling Wheelchair Using Electroencephalogram
	International Journal of Computer Science and Information Security, 2010

[109]	Feature extraction of motor imagery EEG based on wavelet transform and higher-order statistics
	International Journal of Wavelets, Multiresolution and Information Processing, 2010

[110]	Signal Processing and Classification Approaches for Brain-computer Interface
	Intelligent and Biosensors, Edited by Vernon S. Somerset?, 2010

[111]	DEVELOPING A BRAIN-COMPUTER-BASED HUMAN-ROBOT INTERACTION FOR INDUSTRIAL ENVIRONMENTS.
	M DUGULEANA - Annals of DAAAM & Proceedings, 2009, 2009

[112]	Developing a brain-computer-based human-robot interaction for industrial environments
	Annals of DAAAM & Proceedings, 2009

[1]	Deep neural network with harmony search based optimal feature selection of EEG signals for motor imagery classification International Journal of Information Technology, 2023 DOI:10.1007/s41870-021-00857-x

[2]	A multiwavelet-based sparse time-varying autoregressive modeling for motor imagery EEG classification Computers in Biology and Medicine, 2023 DOI:10.1016/j.compbiomed.2022.106196

[3]	Connectivity Analysis in EEG Data: A Tutorial Review of the State of the Art and Emerging Trends Bioengineering, 2023 DOI:10.3390/bioengineering10030372

[4]	Deep neural network with harmony search based optimal feature selection of EEG signals for motor imagery classification International Journal of Information Technology, 2023 DOI:10.1007/s41870-021-00857-x

[5]	Motor imagery EEG signal classification using long short-term memory deep network and neighbourhood component analysis International Journal of Information Technology, 2022 DOI:10.1007/s41870-022-00866-4

[6]	Manual 3D Control of an Assistive Robotic Manipulator Using Alpha Rhythms and an Auditory Menu: A Proof-of-Concept Signals, 2022 DOI:10.3390/signals3020024

[7]	A New PLV-Spatial Filtering to Improve the Classification Performance in BCI Systems IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2022 DOI:10.1109/TNSRE.2022.3198021

[8]	An approach to EEG based BCI for motor imagery using time-frequency representation and CNN 2022 29th International Conference on Systems, Signals and Image Processing (IWSSIP), 2022 DOI:10.1109/IWSSIP55020.2022.9854448

[9]	A multiwavelet-based sparse time-varying autoregressive modeling for motor imagery EEG classification Computers in Biology and Medicine, 2022 DOI:10.1016/j.compbiomed.2022.106196

[10]	EEG Channel Selection Techniques in Motor Imagery Applications: A Review and New Perspectives Bioengineering, 2022 DOI:10.3390/bioengineering9120726

[11]	A multiwavelet-based sparse time-varying autoregressive modeling for motor imagery EEG classification Computers in Biology and Medicine, 2022 DOI:10.1016/j.compbiomed.2022.106196

[12]	Deep neural network with harmony search based optimal feature selection of EEG signals for motor imagery classification International Journal of Information Technology, 2022 DOI:10.1007/s41870-021-00857-x

[13]	Biosignal Processing and Classification Using Computational Learning and Intelligence 2022 DOI:10.1016/B978-0-12-820125-1.00014-2

[14]	Optimum Order Selection Criterion for Autoregressive Models of Bandlimited EEG Signals 2020 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES), 2021 DOI:10.1109/IECBES48179.2021.9398836

[15]	Analysis of EEG-Based Stroke Severity Groups Clustering using K-Means 2021 International Seminar on Intelligent Technology and Its Applications (ISITIA), 2021 DOI:10.1109/ISITIA52817.2021.9502250

[16]	Brain-Computer Interface: Advancement and Challenges Sensors, 2021 DOI:10.3390/s21175746

[17]	Motor Imagery: A Review of Existing Techniques, Challenges and Potentials 2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC), 2021 DOI:10.1109/COMPSAC51774.2021.00286

[18]	Fuzzy support vector machine with joint optimization of genetic algorithm and fuzzy c-means Technology and Health Care, 2021 DOI:10.3233/THC-202619

[19]	Biomedical and Clinical Engineering for Healthcare Advancement Advances in Bioinformatics and Biomedical Engineering, 2020 DOI:10.4018/978-1-7998-0326-3.ch009

[20]	Statistical Analysis of Subject-Specific EEG data during Stroke Rehabilitation Monitoring 2020 10th Electrical Power, Electronics, Communications, Controls and Informatics Seminar (EECCIS), 2020 DOI:10.1109/EECCIS49483.2020.9263462

[21]	Statistical Analysis for EEG Patterns Comparison Between Real Motion and Imagery Motion 2020 10th Electrical Power, Electronics, Communications, Controls and Informatics Seminar (EECCIS), 2020 DOI:10.1109/EECCIS49483.2020.9263451

[22]	Advances in Emerging Trends and Technologies Advances in Intelligent Systems and Computing, 2020 DOI:10.1007/978-3-030-32033-1_2

[23]	YAPAY SİNİR AĞLARI KULLANILARAK İMLEÇ YÖNÜ TESPİTİ Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 2020 DOI:10.28948/ngumuh.681241

[24]	Analysis of the EEG Rhythms Based on the Empirical Mode Decomposition During Motor Imagery When Using a Lower-Limb Exoskeleton. A Case Study Frontiers in Neurorobotics, 2020 DOI:10.3389/fnbot.2020.00048

[25]	An Improved Composite Multiscale Fuzzy Entropy for Feature Extraction of MI-EEG Entropy, 2020 DOI:10.3390/e22121356

[26]	Reducing Sensors in Mental Imagery Based Cognitive Task for Brain Computer Interface 2020 14th International Conference on Signal Processing and Communication Systems (ICSPCS), 2020 DOI:10.1109/ICSPCS50536.2020.9310065

[27]	Combined CNN and LSTM for Motor Imagery Classification 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), 2019 DOI:10.1109/CISP-BMEI48845.2019.8965653

[28]	Wavelet transform based approach for EEG feature selection of motor imagery data for braincomputer interfaces 2019 Third International Conference on Inventive Systems and Control (ICISC), 2019 DOI:10.1109/ICISC44355.2019.9036445

[29]	Hardware-Software Complex of the Mobile Brain-Computer Interface for Technical Means of Rehabilitation 2019 International Conference on Electrotechnical Complexes and Systems (ICOECS), 2019 DOI:10.1109/ICOECS46375.2019.8949968

[30]	Classification of Motor Imagery Tasks using Phase Space Reconstruction and Empirical Mode Decomposition 2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE), 2019 DOI:10.1109/CCECE.2019.8861732

[31]	Classification of Motor Imagery Activities Using Band Power and Second Order Difference Plot 2019 IEEE Bombay Section Signature Conference (IBSSC), 2019 DOI:10.1109/IBSSC47189.2019.8973077

[32]	Filtering techniques for channel selection in motor imagery EEG applications: a survey Artificial Intelligence Review, 2019 DOI:10.1007/s10462-019-09694-8

[33]	Evaluation of quantitative and qualitative features for the acoustic analysis of domestic dogs’ vocalizations Journal of Intelligent & Fuzzy Systems, 2019 DOI:10.3233/JIFS-179050

[34]	EMBEC & NBC 2017 IFMBE Proceedings, 2018 DOI:10.1007/978-981-10-5122-7_58

[35]	An Experimental Analysis of Motor Imagery EEG Signals Using Feature Extraction and Classification Methodologies 2018 International Conference on Computing, Power and Communication Technologies (GUCON), 2018 DOI:10.1109/GUCON.2018.8675032

[36]	Motor imagery based on adaptive parameterless empirical wavelet transform and selective integrated classification Acta Physica Sinica, 2018 DOI:10.7498/aps.67.20180181

[37]	Classification of Motor Imagery Tasks Using Inter Trial Variance In The Brain Computer Interface 2018 IEEE International Symposium on Medical Measurements and Applications (MeMeA), 2018 DOI:10.1109/MeMeA.2018.8438648

[38]	Fuzzy Systems 2017 DOI:10.4018/978-1-5225-1908-9.ch016

[39]	Cost-efficient brainwave controller for automated vehicles route decisions 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC), 2017 DOI:10.1109/ITSC.2017.8317949

[40]	Gaze controlled prosthetic arm with EMG and EEG input interface 2017 21st European Microelectronics and Packaging Conference (EMPC) & Exhibition, 2017 DOI:10.23919/EMPC.2017.8346906

[41]	Evolving multi-dimensional wavelet neural networks for classification using Cartesian Genetic Programming Neurocomputing, 2017 DOI:10.1016/j.neucom.2017.03.048

[42]	Towards sign language recognition using EEG-based motor imagery brain computer interface 2017 5th International Winter Conference on Brain-Computer Interface (BCI), 2017 DOI:10.1109/IWW-BCI.2017.7858143

[43]	Progress in EEG-Based Brain Robot Interaction Systems Computational Intelligence and Neuroscience, 2017 DOI:10.1155/2017/1742862

[44]	Influences of the signal border extension in the discrete wavelet transform in EEG spike detection Research on Biomedical Engineering, 2016 DOI:10.1590/2446-4740.01815

[45]	Design and development of EEG controlled mobile robots 2016 IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT), 2016 DOI:10.1109/ICAECCT.2016.7942569

[46]	Classification of motor imagery movements using multivariate empirical mode decomposition and short time Fourier transform based hybrid method Engineering Science and Technology, an International Journal, 2016 DOI:10.1016/j.jestch.2016.04.009

[47]	Mixture of autoregressive modeling orders and its implication on single trial EEG classification Expert Systems with Applications, 2016 DOI:10.1016/j.eswa.2016.08.044

[48]	Brain-Computer Interface controlled functional electrical stimulation system for paralyzed arm 2016 8th Cairo International Biomedical Engineering Conference (CIBEC), 2016 DOI:10.1109/CIBEC.2016.7836117

[49]	Multiscale AM-FM methods on EEG signals for motor task classification 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015 DOI:10.1109/EMBC.2015.7319811

[50]	A feature extraction method based on dictionary learning for EEG 2015 11th International Conference on Natural Computation (ICNC), 2015 DOI:10.1109/ICNC.2015.7378137

[51]	Robotic neurorehabilitation system design for stroke patients Advances in Mechanical Engineering, 2015 DOI:10.1177/1687814015573768

[52]	Evaluation of local field potential signals in decoding of visual attention Cognitive Neurodynamics, 2015 DOI:10.1007/s11571-015-9336-2

[53]	Entropy Analysis as an Electroencephalogram Feature Extraction Method Science and Education of the Bauman MSTU, 2014 DOI:10.7463/1114.0739919

[54]	Motor Imagery EEG Classification Method using EMD and FFT Journal of KIISE, 2014 DOI:10.5626/JOK.2014.41.12.1050

[55]	Classifications of motor imagery tasks using k-nearest neighbors 12th Symposium on Neural Network Applications in Electrical Engineering (NEUREL), 2014 DOI:10.1109/NEUREL.2014.7011475

[56]	Sub-band-power-based efficient Brain Computer Interface for wheelchair control 2014 World Symposium on Computer Applications & Research (WSCAR), 2014 DOI:10.1109/WSCAR.2014.6916840

[57]	Multiresolution analysis over simple graphs for brain computer interfaces Journal of Neural Engineering, 2013 DOI:10.1088/1741-2560/10/4/046014

[58]	Novel use of Empirical Mode Decomposition in single-trial classification of motor imagery for use in brain-computer interfaces 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2013 DOI:10.1109/EMBC.2013.6610822

[59]	Multi-objective metaheuristics for preprocessing EEG data in brain–computer interfaces Engineering Optimization, 2012 DOI:10.1080/0305215X.2011.641542

[60]	A BCI motor imagery experiment based on parametric feature extraction and Fisher Criterion CONIELECOMP 2012, 22nd International Conference on Electrical Communications and Computers, 2012 DOI:10.1109/CONIELECOMP.2012.6189920

[61]	Spectral analysis of EEG signals generated from imagined writing 2012 IEEE 8th International Colloquium on Signal Processing and its Applications, 2012 DOI:10.1109/CSPA.2012.6194782

[62]	FEATURE EXTRACTION OF MOTOR IMAGERY EEG BASED ON WAVELET TRANSFORM AND HIGHER-ORDER STATISTICS International Journal of Wavelets, Multiresolution and Information Processing, 2010 DOI:10.1142/S0219691310003535

Follow SCIRP

	+1 323-425-8868
	customer@scirp.org
	+86 18163351462(WhatsApp)
	1655362766

	Paper Publishing WeChat

Journal of Biomedical Science and Engineering

Journal of Biomedical Science and Engineering

Journals Menu

Home

About SCIRP

Service

Policies