EEG-Based Brain-Computer Interface for Decoding Motor Imagery Tasks within the Same Hand Using Choi-Williams Time-Frequency Distribution
暂无分享,去创建一个
Mohammad I. Daoud | Rami Alazrai | Hisham Alwanni | Yara Baslan | Nasim Alnuman | Nasim Alnuman | M. Daoud | R. Alazrai | Hisham Alwanni | Yara Baslan
[1] G. R. Muller,et al. Brain oscillations control hand orthosis in a tetraplegic , 2000, Neuroscience Letters.
[2] A. Flisberg,et al. Automatic classification of background EEG activity in healthy and sick neonates , 2010, Journal of neural engineering.
[3] Gernot R. Müller-Putz,et al. Control of an Electrical Prosthesis With an SSVEP-Based BCI , 2008, IEEE Transactions on Biomedical Engineering.
[4] Joerg F. Hipp,et al. Time-Frequency Analysis , 2014, Encyclopedia of Computational Neuroscience.
[5] Paolo Castiglioni. Choi–Williams Distribution , 2005 .
[6] E Donchin,et al. The mental prosthesis: assessing the speed of a P300-based brain-computer interface. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.
[7] John M. O'Toole,et al. Time-Frequency Processing of Nonstationary Signals: Advanced TFD Design to Aid Diagnosis with Highlights from Medical Applications , 2013, IEEE Signal Processing Magazine.
[8] Boualem Boashash,et al. Principles of time-frequency feature extraction for change detection in non-stationary signals: Applications to newborn EEG abnormality detection , 2015, Pattern Recognit..
[9] Bin He,et al. EEG Control of a Virtual Helicopter in 3-Dimensional Space Using Intelligent Control Strategies , 2010, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[10] Jonathan R Wolpaw,et al. A brain-computer interface for long-term independent home use , 2010, Amyotrophic lateral sclerosis : official publication of the World Federation of Neurology Research Group on Motor Neuron Diseases.
[11] Dean J Krusienski,et al. Brain-computer interfaces in medicine. , 2012, Mayo Clinic proceedings.
[12] U. Rajendra Acharya,et al. Application of entropies for automated diagnosis of epilepsy using EEG signals: A review , 2015, Knowl. Based Syst..
[13] Trent J. Bradberry,et al. Reconstructing Three-Dimensional Hand Movements from Noninvasive Electroencephalographic Signals , 2010, The Journal of Neuroscience.
[14] Zhilin Zhang,et al. Evolving Signal Processing for Brain–Computer Interfaces , 2012, Proceedings of the IEEE.
[15] S. Hahn. Hilbert Transforms in Signal Processing , 1996 .
[16] Francisco Sepulveda,et al. Delta band contribution in cue based single trial classification of real and imaginary wrist movements , 2008, Medical & Biological Engineering & Computing.
[17] Dennis J. McFarland,et al. Brain–computer interfaces for communication and control , 2002, Clinical Neurophysiology.
[18] M. Peters,et al. Volume conduction effects in EEG and MEG. , 1998, Electroencephalography and clinical neurophysiology.
[19] Somaya Al-Máadeed,et al. On the use of time-frequency features for detecting and classifying epileptic seizure activities in non-stationary EEG signals , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[20] L. Cohen,et al. Time-frequency distributions-a review , 1989, Proc. IEEE.
[21] Scott T. Grafton,et al. Localization of grasp representations in humans by positron emission tomography , 1996, Experimental Brain Research.
[22] Bangyan Zhou,et al. A Fully Automated Trial Selection Method for Optimization of Motor Imagery Based Brain-Computer Interface , 2016, PloS one.
[23] W. De Clercq,et al. Automatic Removal of Ocular Artifacts in the EEG without an EOG Reference Channel , 2006, Proceedings of the 7th Nordic Signal Processing Symposium - NORSIG 2006.
[24] Anant Madabhushi,et al. Cascaded multi-class pairwise classifier (CascaMPa) for normal, cancerous, and cancer confounder classes in prostate histology , 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.
[25] Qing Yang,et al. A Brain-Computer Interface Based on a Few-Channel EEG-fNIRS Bimodal System , 2017, IEEE Access.
[26] Chao Li,et al. A Brain-Machine Interface Based on ERD/ERS for an Upper-Limb Exoskeleton Control , 2016, Sensors.
[27] A. Doud,et al. Continuous Three-Dimensional Control of a Virtual Helicopter Using a Motor Imagery Based Brain-Computer Interface , 2011, PloS one.
[28] Manfredo Atzori,et al. Electromyography data for non-invasive naturally-controlled robotic hand prostheses , 2014, Scientific Data.
[29] Bin He,et al. EEG Source Imaging Enhances the Decoding of Complex Right-Hand Motor Imagery Tasks , 2016, IEEE Transactions on Biomedical Engineering.
[30] G. Pfurtscheller,et al. Graz-BCI: state of the art and clinical applications , 2003, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[31] Hans-Jochen Heinze,et al. Single trial discrimination of individual finger movements on one hand: A combined MEG and EEG study , 2012, NeuroImage.
[32] Ke Liao,et al. Decoding Individual Finger Movements from One Hand Using Human EEG Signals , 2014, PloS one.
[33] Eli M. Mizrahi,et al. A Multi-stage System for the Automated Detection of Epileptic Seizures in Neonatal EEG , 2009 .
[34] N. Birbaumer. Breaking the silence: brain-computer interfaces (BCI) for communication and motor control. , 2006, Psychophysiology.
[35] Boualem Boashash,et al. Automatic signal abnormality detection using time-frequency features and machine learning: A newborn EEG seizure case study , 2016, Knowl. Based Syst..
[36] S. Coyle,et al. Brain–computer interfaces: a review , 2003 .
[37] LJubisa Stankovic,et al. A measure of some time-frequency distributions concentration , 2001, Signal Process..
[38] G. Lightbody,et al. A comparison of quantitative EEG features for neonatal seizure detection , 2008, Clinical Neurophysiology.
[39] Ulrich H.-G. Kreßel,et al. Pairwise classification and support vector machines , 1999 .
[40] Carlo Menon,et al. EEG Classification of Different Imaginary Movements within the Same Limb , 2015, PloS one.
[41] Carlos Guerrero-Mosquera,et al. New feature extraction approach for epileptic EEG signal detection using time-frequency distributions , 2010, Medical & Biological Engineering & Computing.
[42] Tian Lan,et al. Salient EEG Channel Selection in Brain Computer Interfaces by Mutual Information Maximization , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.
[43] Mohammed Imamul Hassan Bhuiyan,et al. Detection of Seizure and Epilepsy Using Higher Order Statistics in the EMD Domain , 2013, IEEE Journal of Biomedical and Health Informatics.
[44] Chih-Jen Lin,et al. A comparison of methods for multiclass support vector machines , 2002, IEEE Trans. Neural Networks.
[45] Gert Pfurtscheller,et al. Motor imagery and direct brain-computer communication , 2001, Proc. IEEE.
[46] M. Jeannerod. Mental imagery in the motor context , 1995, Neuropsychologia.
[47] William J. Williams,et al. Improved time-frequency representation of multicomponent signals using exponential kernels , 1989, IEEE Trans. Acoust. Speech Signal Process..
[48] Lei Ding,et al. Motor imagery classification by means of source analysis for brain–computer interface applications , 2004, Journal of neural engineering.
[49] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[50] Mj Martin Bastiaans. Time-frequency signal analysis , 2008 .
[51] K. Lafleur,et al. Quadcopter control in three-dimensional space using a noninvasive motor imagery-based brain–computer interface , 2013, Journal of neural engineering.
[52] S. M. Debbal,et al. Time-frequency analysis of the first and the second heartbeat sounds , 2007, Appl. Math. Comput..
[53] Pablo M. Granitto,et al. Cascade classifiers for multiclass problems , 2005 .
[54] Jonathan R Wolpaw,et al. Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans. , 2004, Proceedings of the National Academy of Sciences of the United States of America.
[55] Ruimin Wang,et al. Classification of Four-Class Motor Imagery Employing Single-Channel Electroencephalography , 2014, PloS one.
[56] Dimitrios I. Fotiadis,et al. Epileptic Seizure Detection in EEGs Using Time–Frequency Analysis , 2009, IEEE Transactions on Information Technology in Biomedicine.
[57] Mohammed Imamul Hassan Bhuiyan,et al. On the classification of sleep states by means of statistical and spectral features from single channel Electroencephalogram , 2015, 2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI).
[58] Boualem Boashash,et al. Time-Frequency Signal Analysis and Processing: A Comprehensive Reference , 2015 .
[59] Rami Alazrai,et al. Fall Detection for Elderly from Partially Observed Depth-Map Video Sequences Based on View-Invariant Human Activity Representation , 2017 .
[60] Niels Birbaumer,et al. fMRI Brain-Computer Interface: A Tool for Neuroscientific Research and Treatment , 2007, Comput. Intell. Neurosci..
[61] G. Buccino,et al. Action observation versus motor imagery in learning a complex motor task: A short review of literature and a kinematics study , 2013, Neuroscience Letters.
[62] Kalyana Chakravarthy Veluvolu,et al. Time-Frequency Analysis of Non-Stationary Biological Signals with Sparse Linear Regression Based Fourier Linear Combiner , 2017, Sensors.
[63] Francisco Sepulveda,et al. Classifying mental tasks based on features of higher-order statistics from EEG signals in brain-computer interface , 2008, Inf. Sci..
[64] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[65] Michael I. Jordan,et al. On Discriminative vs. Generative Classifiers: A comparison of logistic regression and naive Bayes , 2001, NIPS.
[66] Christa Neuper,et al. An asynchronously controlled EEG-based virtual keyboard: improvement of the spelling rate , 2004, IEEE Transactions on Biomedical Engineering.
[67] U. Rajendra Acharya,et al. Automated detection and localization of myocardial infarction using electrocardiogram: a comparative study of different leads , 2016, Knowl. Based Syst..
[68] Xingyu Wang,et al. Optimized Motor Imagery Paradigm Based on Imagining Chinese Characters Writing Movement , 2016, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[69] Arnaud Delorme,et al. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis , 2004, Journal of Neuroscience Methods.
[70] Zhiquan Wang,et al. Recognition of human activities using SVM multi-class classifier , 2010, Pattern Recognit. Lett..