Adaptive-projection intrinsically transformed multivariate empirical mode decomposition in cooperative brain–computer interface applications [PDF]
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2016 An extension to multivariate empirical mode decomposition (MEMD), termed adaptive-projection intrinsically transformed MEMD (APIT-MEMD), is proposed to cater for power imbalances and inter-channel correlations in real-world multichannel data. It is shown that the APIT-MEMD exhibits similar or better performance than MEMD for a large number of ...
Apit Hemakom +3 more
semanticscholar +7 more sources
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 ...
Yi-Feng Chen +3 more
semanticscholar +5 more sources
Dual-Mode Visual System for Brain-Computer Interfaces: Integrating SSVEP and P300 Responses. [PDF]
Sensors (Basel)In 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 ...
Kasawala E, Mouli S.
europepmc +5 more sources
A Dual-Mode Human Computer Interface Combining Speech and Tongue Motion for People with Severe Disabilities [PDF]
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2013 We are presenting a new wireless and wearable human computer interface called the dual-mode Tongue Drive System (dTDS), which is designed to allow people with severe disabilities to use computers more effectively with increased speed, flexibility, usability, and independence through their tongue motion and speech.
Xueliang Huo +3 more
semanticscholar +5 more sources
An Automatic Subject Specific Intrinsic Mode Function Selection for Enhancing Two-Class EEG-Based Motor Imagery-Brain Computer Interface [PDF]
IEEE Sensors Journal, 2019 The electroencephalogram (EEG) signals tend to have poor time-frequency localization when analysis techniques involve a fixed set of basis functions such as in short-time Fourier transform and wavelet transform.
Pramod Gaur +3 more
semanticscholar +4 more sources
2015 International Joint Conference on Neural Networks (IJCNN), 2015 In this paper, we present a new filtering method based on the empirical mode decomposition (EMD) for classification of motor imagery (MI) electroencephalogram (EEG) signals for enhancing brain-computer interface (BCI). The EMD method decomposes EEG signals into a set of intrinsic mode functions (IMFs).
Pramod Gaur +3 more
semanticscholar +5 more sources
BRAIN-COMPUTER INTERFACE: COMPARISON OF TWO CONTROL MODES TO DRIVE A VIRTUAL ROBOT [PDF]
, 2015 A Brain-Computer Interface (BCI) is a system that enables communication and control that is not based on muscular movements, but on brain activity. Some of these systems are based on discrimination of different mental tasks; usually they match the number
Ricardo Ron-Angevín +4 more
core +6 more sources
IEEE Journal of Solid-State Circuits, 2021 This article presents a multipolar neural stimulation and mixed-signal neural data acquisition (DAQ) chipset for fully implantable bi-directional brain–computer interfaces (BD-BCIs). The stimulation system employs four 40 V compliant current-stimulators,
Haoran Pu +5 more
openalex +2 more sources
Non-invasive brain-to-brain interface (BBI): establishing functional links between two brains. [PDF]
PLoS ONE, 2013 Transcranial focused ultrasound (FUS) is capable of modulating the neural activity of specific brain regions, with a potential role as a non-invasive computer-to-brain interface (CBI).
Seung-Schik Yoo +4 more
doaj +7 more sources
An Exploration of Effects of Dark Mode on University Students: A Human Computer Interface Analysis [PDF]
none
Awan Shrestha +6 more
+6 more sources