Journal ArticleDOI
Classification of motor imagery by means of cortical current density estimation and Von Neumann entropy
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TLDR
The results confirm the hypothesis that source analysis methods may improve accuracy for classification of motor imagery tasks and enhances the ability of performing source analysis from single trial EEG data recorded on the scalp, and may have applications to improved BCI systems.Abstract:
The goal of the present study is to employ the source imaging methods such as cortical current density estimation for the classification of left- and right-hand motor imagery tasks, which may be used for brain-computer interface (BCI) applications. The scalp recorded EEG was first preprocessed by surface Laplacian filtering, time-frequency filtering, noise normalization and independent component analysis. Then the cortical imaging technique was used to solve the EEG inverse problem. Cortical current density distributions of left and right trials were classified from each other by exploiting the concept of Von Neumann entropy. The proposed method was tested on three human subjects (180 trials each) and a maximum accuracy of 91.5% and an average accuracy of 88% were obtained. The present results confirm the hypothesis that source analysis methods may improve accuracy for classification of motor imagery tasks. The present promising results using source analysis for classification of motor imagery enhances our ability of performing source analysis from single trial EEG data recorded on the scalp, and may have applications to improved BCI systems.read more
Citations
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Journal ArticleDOI
Brain–Computer Interfaces Using Sensorimotor Rhythms: Current State and Future Perspectives
TL;DR: The current state and future perspectives of SMR-based BCI and its clinical applications are reviewed, in particular focusing on the EEG SMR.
Journal ArticleDOI
EEG Source Imaging Enhances the Decoding of Complex Right-Hand Motor Imagery Tasks
TL;DR: This study extends previous EEG source imaging work to decoding natural hand/wrist manipulations by applying a novel technique to classifying four complex motor imaginations of the right hand: flexion, extension, supination, and pronation, and suggests ESI is able to enhance BCI performance of decoding complex right-hand motor imagery tasks.
Journal ArticleDOI
Negative covariation between task-related responses in alpha/beta-band activity and BOLD in human sensorimotor cortex: an EEG and fMRI study of motor imagery and movements.
TL;DR: Task-induced increase of BOLD signal and decrease of EEG amplitudes in alpha and beta bands were shown to be co-localized at the somatotopic sensorimotor cortex, suggesting an inverse functional coupling relationship between task-induced changes of Bold and low-frequency EEG signals.
Journal ArticleDOI
Neurofeedback-based motor imagery training for brain–computer interface (BCI)
TL;DR: The proposed neurofeedback-based motor imagery training system can help individuals get the feel of motor imagery by presenting them with real-time brain activation maps on their cortex and will be useful not only for BCI applications, but for functional brain mapping studies that utilize motor imagery tasks as well.
Journal ArticleDOI
Continuous three-dimensional control of a virtual helicopter using a motor imagery based brain-computer interface.
TL;DR: The results affirm the effective, three-dimensional control of the motor imagery based BCI system, and suggest its potential applications in biological navigation, neuroprosthetics, and other applications.
References
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TL;DR: In this article, the quantum Fourier transform and its application in quantum information theory is discussed, and distance measures for quantum information are defined. And quantum error-correction and entropy and information are discussed.
Quantum Computation and Quantum Information
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Independent component analysis, a new concept?
TL;DR: An efficient algorithm is proposed, which allows the computation of the ICA of a data matrix within a polynomial time and may actually be seen as an extension of the principal component analysis (PCA).
Journal ArticleDOI
Brain-computer interfaces for communication and control.
Jonathan R. Wolpaw,Jonathan R. Wolpaw,Niels Birbaumer,Niels Birbaumer,Dennis J. McFarland,Gert Pfurtscheller,Theresa M. Vaughan +6 more
TL;DR: With adequate recognition and effective engagement of all issues, BCI systems could eventually provide an important new communication and control option for those with motor disabilities and might also give those without disabilities a supplementary control channel or a control channel useful in special circumstances.
Journal ArticleDOI
Analysis of discrete ill-posed problems by means of the L-curve
TL;DR: The main purpose of this paper is to advocate the use of the graph associated with Tikhonov regularization in the numerical treatment of discrete ill-posed problems, and to demonstrate several important relations between regularized solutions and the graph.