Results 31 to 40 of about 648,377 (206)
Brain Sciences, 2023 Joint attention skills deficiency in Autism spectrum disorder (ASD) hinders individuals from communicating effectively. The P300 Electroencephalogram (EEG) signal-based brain–computer interface (BCI) helps these individuals in neurorehabilitation ...
Santhosh Peketi, Sanjay B. Dhok
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A model for the control mode man-computer interface dialogue [PDF]
, 1981 A four stage model is presented for the control mode man-computer interface dialogue. It consists of context development, semantic development syntactic development, and command execution.
Chafin, R. L.
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A Synchronous Motor Imagery Based Neural Physiological Paradigm for Brain Computer Interface Speller
Frontiers in Human Neuroscience, 2017 Brain Computer Interface (BCI) speller is a typical BCI-based application to help paralyzed patients express their thoughts. This paper proposed a novel motor imagery based BCI speller with Oct-o-spell paradigm for word input. Furthermore, an intelligent
Lei Cao +8 more
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Shared Three-Dimensional Robotic Arm Control Based on Asynchronous BCI and Computer Vision
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023 Objective: A brain-computer interface (BCI) can be used to translate neuronal activity into commands to control external devices. However, using noninvasive BCI to control a robotic arm for movements in three-dimensional (3D) environments and accomplish ...
Yajun Zhou +6 more
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A simple beam model for the shear failure of interfaces [PDF]
, 2005 We propose a novel model for the shear failure of a glued interface between two solid blocks. We model the interface as an array of elastic beams which experience stretching and bending under shear load and break if the two deformation modes exceed ...
Herrmann, H. J., Kun, F., Raischel, F.
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Dual-Mode Visual System for Brain–Computer Interfaces: Integrating SSVEP and P300 Responses
SensorsIn brain–computer interface (BCI) systems, steady-state visual-evoked potentials (SSVEP) and P300 responses have achieved widespread implementation owing to their superior information transfer rates (ITR) and minimal training requirements. These neurophysiological signals have exhibited robust efficacy and versatility in external device control ...
Ekgari Kasawala, Surej Mouli
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EEG Signals Feature Extraction Based on DWT and EMD Combined with Approximate Entropy
Brain Sciences, 2019 The classification recognition rate of motor imagery is a key factor to improve the performance of brain−computer interface (BCI). Thus, we propose a feature extraction method based on discrete wavelet transform (DWT), empirical mode decomposition (
Na Ji, Liang Ma, Hui Dong, Xuejun Zhang
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IEEE Access, 2018 Considering the difficult maneuverability of the hovercraft and the driving burden of the pilot, an automatic tracking system including an intuitive human-computer interface and an adaptive chattering-free full-order terminal sliding mode (ACFTSM ...
Mingyu Fu +3 more
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A new multivariate empirical mode decomposition method for improving the performance of SSVEP-based brain–computer interface [PDF]
Journal of Neural Engineering, 2017 Accurate and efficient detection of steady-state visual evoked potentials (SSVEP) in electroencephalogram (EEG) is essential for the related brain-computer interface (BCI) applications.Although the canonical correlation analysis (CCA) has been applied extensively and successfully to SSVEP recognition, the spontaneous EEG activities and artifacts that ...
Chen, Y-F, Atal, K, Xie, S-Q, Liu, Q
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, 2012 The paper presents a pilot study conducted with spatial visual, audiovisual and auditory brain-computer-interface (BCI) based speller paradigms. The psychophysical experiments are conducted with healthy subjects in order to evaluate a difficulty and a ...
Cai, Zhenyu +4 more
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