Proceedings ArticleDOI
Motor imagery based BCI for a maze game
Simanta Bordoloi,Ujjal Sharmah,Shyamanta M. Hazarika +2 more
- pp 1-6
TLDR
A BCI maze game is designed and developed, where a player plays the game in real time using his brain signals using two hybrid features of bispectrum of EEG through a RBF kernel support vector machine.Abstract:
Electroencephalogram (EEG) signals generated out of motor imagery (MI) can be used for Brain Computer Interfacing (BCI). In order to accomplish this goal, we have classified four different MI tasks using two hybrid features of bispectrum of EEG through a RBF kernel support vector machine. As a demonstration of its applicability for a non-invasive BCI, we design and develop a BCI maze game, where a player plays the game in real time using his brain signals.read more
Citations
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Journal ArticleDOI
EEG-based BCI and video games: a progress report
TL;DR: The paper examines the progress of BCI research with regard to games and shows that gaming applications offer numerous advantages by orienting BCI to concerns and expectations of a gaming application.
Journal ArticleDOI
Bispectrum-Based Channel Selection for Motor Imagery Based Brain-Computer Interfacing
TL;DR: Compared to the other state-of-the-art methods, the proposed bispectrum-based channel selection (BCS) method can achieve significantly better classification accuracies for MI-based BCI (Wilcoxon signed test, p < 0.05).
Journal ArticleDOI
Motor imagery, P300 and error-related EEG-based robot arm movement control for rehabilitation purpose.
TL;DR: A novel approach toward EEG-driven position control of a robot arm is proposed by utilizing motor imagery, P300 and error-related potentials (ErRP) to align the robot arm with desired target position.
Journal ArticleDOI
Interval type-2 fuzzy logic based multiclass ANFIS algorithm for real-time EEG based movement control of a robot arm
TL;DR: A multi-class discriminating algorithm based on the fusion of interval type-2 fuzzy logic and ANFIS to improve uncertainty handling and the result shows the competitiveness of this algorithm over other standard ones in the domain of non-stationary and uncertain signal data classification.
Journal ArticleDOI
CSP-TSM: Optimizing the performance of Riemannian tangent space mapping using common spatial pattern for MI-BCI
TL;DR: The proposed CSP-TSM framework for classification of EEG signals for MI-BCI gives improved performance in comparison with several competing methods and the computational complexity is less compared to that of TSM method.
References
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Electroencephalography: Basic Principles, Clinical Applications and Related Fields, Fourth Edition
TL;DR: Historical aspects introduction to the neurophysiological basis of the EEG and DC potentials cellular substrates of spontaneous and evoked brain rhythms dynamics of EEG as signals and neuronal populations are introduced.
Book
Electroencephalography: Basic Principles, Clinical Applications, and Related Fields
TL;DR: The main thrust of Electroencephalography is to preserve the sound basis of classic EEG recording and reading and, on the other hand, to present the newest developments for future EEG/neurophysiology research, especially in view of the highest brain functions as mentioned in this paper.
Journal ArticleDOI
Brain–machine interfaces: past, present and future
TL;DR: This paper discusses designing a fully implantable biocompatible recording device, further developing real-time computational algorithms, introducing a method for providing the brain with sensory feedback from the actuators, and designing and building artificial prostheses that can be controlled directly by brain-derived signals.
Journal ArticleDOI
Real-time control of a robot arm using simultaneously recorded neurons in the motor cortex
TL;DR: A possible means for movement restoration in paralysis patients is suggested after rats trained to position a robot arm to obtain water by pressing a lever routinely used brain-derived signals to position the robot arm and obtain water.
Journal ArticleDOI
Brain-computer interface using a simplified functional near-infrared spectroscopy system.
TL;DR: This work describes the construction of the device, the principles of operation and the implementation of a fNIRS-BCI application, 'Mindswitch' that harnesses motor imagery for control, and shows that fNirS can support simple BCI functionality and shows much potential.