Towards improved EEG interpretation in a sensorimotor BCI for the control of a prosthetic or orthotic hand.
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[1] R.P.N. Rao,et al. Finger Movement Classification for an Electrocorticographic BCI , 2007, 2007 3rd International IEEE/EMBS Conference on Neural Engineering.
[2] M. Hallett,et al. A high performance sensorimotor beta rhythm-based brain–computer interface associated with human natural motor behavior , 2008, Journal of neural engineering.
[3] Krishna Mehta,et al. Selecting the Appropriate Outlier Treatment for Common Industry Applications , 2007 .
[4] Febo Cincotti,et al. Modern Electrophysiological Methods for Brain-Computer Interfaces , 2007, Comput. Intell. Neurosci..
[5] 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.
[6] G. Pfurtscheller,et al. Event-related dynamics of cortical rhythms: frequency-specific features and functional correlates. , 2001, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.
[7] Neil M. White,et al. Control Strategies for a Multiple Degree of Freedom Prosthetic Hand , 2006 .
[8] Dario Farina,et al. Single-trial discrimination of type and speed of wrist movements from EEG recordings , 2009, Clinical Neurophysiology.
[9] A. Vuckovic,et al. A four-class BCI based on motor imagination of the right and the left hand wrist , 2008, 2008 First International Symposium on Applied Sciences on Biomedical and Communication Technologies.
[10] F. L. D. Silva,et al. Event-related EEG/MEG synchronization and desynchronization: basic principles , 1999, Clinical Neurophysiology.
[11] Klaus-Robert Müller,et al. Classifying Single Trial EEG: Towards Brain Computer Interfacing , 2001, NIPS.
[12] G. Pfurtscheller,et al. Patterns of cortical activation during planning of voluntary movement. , 1989, Electroencephalography and clinical neurophysiology.
[13] Ton Kalker,et al. A Highly Robust Audio Fingerprinting System , 2002, ISMIR.
[14] M Congedo,et al. A review of classification algorithms for EEG-based brain–computer interfaces , 2007, Journal of neural engineering.
[15] Andreas Schulze-Bonhage,et al. Prediction of arm movement trajectories from ECoG-recordings in humans , 2008, Journal of Neuroscience Methods.
[16] Clemens Brunner,et al. Mu rhythm (de)synchronization and EEG single-trial classification of different motor imagery tasks , 2006, NeuroImage.
[17] Ian T. Nabney,et al. Netlab: Algorithms for Pattern Recognition , 2002 .
[18] Michele G. Jarrell,et al. A Comparison of Two Procedures, the Mahalanobis Distance and the Andrews-Pregibon Statistic, for Identifying Multivariate Outliers. , 1992 .
[19] E. Fetz,et al. Decoupling the Cortical Power Spectrum Reveals Real-Time Representation of Individual Finger Movements in Humans , 2009, The Journal of Neuroscience.
[20] Clemens Brunner,et al. Spatial filtering and selection of optimized components in four class motor imagery EEG data using independent components analysis , 2007, Pattern Recognit. Lett..
[21] Francisco Sepulveda,et al. Delta band contribution in cue based single trial classification of real and imaginary wrist movements , 2008, Medical & Biological Engineering & Computing.
[22] Giuseppe Baselli,et al. An adaptive neuro-fuzzy method (ANFIS) for estimating single-trial movement-related potentials , 2004, Biological Cybernetics.
[23] S. Makeig,et al. Mining event-related brain dynamics , 2004, Trends in Cognitive Sciences.
[24] Kevin N. Gurney,et al. An introduction to neural networks , 2018 .
[25] Christopher J. James,et al. Extracting Rhythmic Brain Activity for Brain-Computer Interfacing through Constrained Independent Component Analysis , 2007, Comput. Intell. Neurosci..
[26] J. Mouriño,et al. Recognition of imagined hand movements with low resolution surface Laplacian and linear classifiers. , 2001, Medical engineering & physics.
[27] Dario Farina,et al. Movement-Related Cortical Potentials Allow Discrimination of Rate of Torque Development in Imaginary Isometric Plantar Flexion , 2008, IEEE Transactions on Biomedical Engineering.
[28] Yusuf Uzzaman Khan,et al. Brain-computer interface for single-trial eeg classification for wrist movement imagery using spatial filtering in the gamma band , 2010 .
[29] F. Sepulveda,et al. A Comparison of Time, Frequency and ICA Based Features and Five Classifiers for Wrist Movement Classification in EEG Signals , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.
[30] Gernot R. Müller-Putz,et al. EURASIP Journal on Applied Signal Processing 2005:19, 3152–3155 c ○ 2005 Hindawi Publishing Corporation EEG-Based Asynchronous BCI Controls Functional Electrical Stimulation in a Tetraplegic Patient , 2004 .
[31] A Urbano,et al. A high resolution EEG method based on the correction of the surface Laplacian estimate for the subject's variable scalp thickness. , 1997, Electroencephalography and clinical neurophysiology.
[32] Erkki Oja,et al. Independent component analysis: algorithms and applications , 2000, Neural Networks.
[33] Marie-Françoise Lucas,et al. Optimization of wavelets for classification of movement-related cortical potentials generated by variation of force-related parameters , 2007, Journal of Neuroscience Methods.
[34] Rajesh P. N. Rao,et al. Classification of contralateral and ipsilateral finger movements for electrocorticographic brain-computer interfaces. , 2009, Neurosurgical focus.
[35] Rajesh P. N. Rao,et al. Generalized Features for Electrocorticographic BCIs , 2008, IEEE Transactions on Biomedical Engineering.
[36] Johan Wessberg,et al. Evolutionary optimization of classifiers and features for single-trial EEG Discrimination , 2007, Biomedical engineering online.
[37] Frank Nielsen,et al. Bhattacharyya Clustering with Applications to Mixture Simplifications , 2010, 2010 20th International Conference on Pattern Recognition.
[38] Patricia B. Trossman,et al. Occupational Therapy for Physical Dysfunction, 5th edition , 2003 .
[39] J. Turner,et al. Somatotopy of the motor cortex after long-term spinal cord injury or amputation , 2001, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[40] Pedram Afshar,et al. Neural-based control of a robotic hand: evidence for distinct muscle strategies , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.
[41] Mehran Jahed,et al. Real-time intelligent pattern recognition algorithm for surface EMG signals , 2007, Biomedical engineering online.
[42] P. de Chazal,et al. A parametric feature extraction and classification strategy for brain-computer interfacing , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[43] D. H. Plettenburg. Basic requirements for upper extremity prostheses: the WILMER approach , 1998, Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Vol.20 Biomedical Engineering Towards the Year 2000 and Beyond (Cat. No.98CH36286).
[44] Belinda Barton,et al. Medical Statistics: A Guide to SPSS, Data Analysis and Critical Appraisal , 2005 .
[45] Melinda Rybski. Kinesiology for occupational therapy , 2004 .
[46] Riitta Salmelin,et al. Right rolandic activation during speech perception in stutterers: a MEG study , 2005, NeuroImage.
[47] D. Massart,et al. The Mahalanobis distance , 2000 .
[48] G.E. Birch,et al. A general framework for brain-computer interface design , 2003, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[49] Dario Farina,et al. Offline Identification of Imagined Speed of Wrist Movements in Paralyzed ALS Patients from Single-Trial EEG , 2009, Front. Neuropro..
[50] G. Pfurtscheller,et al. Brain-Computer Interfaces for Communication and Control. , 2011, Communications of the ACM.
[51] Rajesh P. N. Rao,et al. Real-Time Classification of Electromyographic Signals for Robotic Control , 2005, AAAI.
[52] Rabab K Ward,et al. A survey of signal processing algorithms in brain–computer interfaces based on electrical brain signals , 2007, Journal of neural engineering.
[53] S. Slobounov,et al. Modulated cortical control of individual fingers in experienced musicians: an EEG study , 2002, Clinical Neurophysiology.
[54] Mark Hallett,et al. Exploration of computational methods for classification of movement intention during human voluntary movement from single trial EEG , 2007, Clinical Neurophysiology.
[55] M. Hallett,et al. Classifying EEG signals preceding right hand, left hand, tongue, and right foot movements and motor imageries , 2008, Clinical Neurophysiology.
[56] Aleksandra Vuckovic,et al. Non-invasive BCI: How far can we get with motor imagination? , 2009, Clinical Neurophysiology.
[57] Gabriel Curio,et al. Speeding up classification of multi-channel brain-computer interfaces: common spatial patterns for slow cortical potentials , 2003, First International IEEE EMBS Conference on Neural Engineering, 2003. Conference Proceedings..
[58] Febo Cincotti,et al. Human Movement-Related Potentials vs Desynchronization of EEG Alpha Rhythm: A High-Resolution EEG Study , 1999, NeuroImage.
[59] Gernot R. Müller-Putz,et al. Self-Paced (Asynchronous) BCI Control of a Wheelchair in Virtual Environments: A Case Study with a Tetraplegic , 2007, Comput. Intell. Neurosci..
[60] M. Hallett,et al. Predicting Movement: When, Which and Where , 2007, 2007 IEEE/ICME International Conference on Complex Medical Engineering.
[61] A. Erfanian,et al. ICA-based classification scheme for EEG-based brain-computer interface: the role of mental practice and concentration skills , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[62] G. Pfurtscheller,et al. Event-related synchronization of mu rhythm in the EEG over the cortical hand area in man , 1994, Neuroscience Letters.
[63] Douglas M. Hawkins. Identification of Outliers , 1980, Monographs on Applied Probability and Statistics.
[64] Y. Matsuoka,et al. Neuromuscular strategies for dynamic finger movements: a robotic approach , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[65] Igor Skrjanc,et al. Identification of the phase code in an EEG during gripping-force tasks: A possible alternative approach to the development of the brain-computer interfaces , 2008, Artif. Intell. Medicine.
[66] M. Hallett,et al. What is the Bereitschaftspotential? , 2006, Clinical Neurophysiology.
[67] Gert Pfurtscheller,et al. Characterization of four-class motor imagery EEG data for the BCI-competition 2005 , 2005, Journal of neural engineering.
[68] F. Babiloni,et al. Mahalanobis distance-based classifiers are able to recognize EEG patterns by using few EEG electrodes , 2001, 2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[69] Robert D. Lipschutz,et al. Targeted muscle reinnervation for real-time myoelectric control of multifunction artificial arms. , 2009, JAMA.
[70] Klaus-Robert Müller,et al. Combining Features for BCI , 2002, NIPS.
[71] G. Pfurtscheller,et al. Continuous EEG classification during motor imagery-simulation of an asynchronous BCI , 2004, IEEE Transactions on Neural Systems and Rehabilitation Engineering.