Results 1 to 10 of about 449,733 (151)

A CMOS Dual-Mode Brain-Computer Interface Chipset With 2-mV Precision Time-Based Charge Balancing and Stimulation-Side Artifact Suppression

IEEE Journal of Solid-State Circuits, 2022
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,
Ahmad Reza Danesh, Zoran Nenadić, Payam Heydari   +2 more
exaly   +2 more sources

A comparative analysis of masking empirical mode decomposition and a neural network with feed-forward and back propagation along with masking empirical mode decomposition to improve the classification performance for a reliable brain-computer interface

Frontiers in Computational Neuroscience, 2022
In general, extraction and classification are used in various fields like image processing, pattern recognition, signal processing, and so on. Extracting effective characteristics from raw electroencephalogram (EEG) signals is a crucial role of the brain-
K C Sriharipriya
exaly   +2 more sources

An Automatic Subject Specific Intrinsic Mode Function Selection for Enhancing Two-Class EEG-Based Motor Imagery-Brain Computer Interface

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.
Ram Bilas Pachori, Pramod Gaur
exaly   +2 more sources

A Dual-Mode Human Computer Interface Combining Speech and Tongue Motion for People with Severe Disabilities

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 ...
Hangue Park, Maysam Ghovanloo, Jeonghee Kim   +2 more
exaly   +2 more sources

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, Lei Cao, Bin Xia, Bin Xia, Oladazimi Maysam, Jie Li, Hong Xie, Niels Birbaumer, Niels Birbaumer   +8 more
doaj   +2 more sources

AgrOmicSo: A client-server interface for accessible large-scale analysis of next-generation sequencing data. [PDF]

PLoS ONE
The analysis of large-scale next-generation sequencing (NGS) data requires substantial computational power, often necessitating the use of high-performance computing (HPC) environments.
Dong-Jun Lee, Tae-Ho Lee, Taesoo Kwon
doaj   +2 more sources

Subject Combination and Electrode Selection in Cooperative Brain-Computer Interface Based on Event Related Potentials

Brain Sciences, 2014
New paradigms are required in Brain-Computer Interface (BCI) systems for the needs and expectations of healthy people. To solve this issue, we explore the emerging field of cooperative BCIs, which involves several users in a single BCI system.
Hubert Cecotti, Bertrand Rivet
doaj   +3 more sources

Adaptive-projection intrinsically transformed multivariate empirical mode decomposition in cooperative brain–computer interface applications

Philosophical Transactions Series A, Mathematical, Physical, and Engineering Sciences, 2016
Danilo P Mandic, Valentin Goverdovsky, Apit Hemakom   +2 more
exaly   +2 more sources

A Self-Paced P300 Healthcare Brain-Computer Interface System with SSVEP-Based Switching Control and Kernel FDA + SVM-Based Detector

Applied Sciences, 2016
This paper presents a novel brain-computer interface (BCI)-based healthcare control system, which is based on steady-state visually evoked potential (SSVEP) and P300 of electroencephalography (EEG) signals. The proposed system is composed of two modes, a
Yi-Hung Liu, Shih-Hao Wang, Ming-Ren Hu
doaj   +2 more sources

A Hybrid Brain-Computer Interface Using Motor Imagery and SSVEP Based on Convolutional Neural Network [PDF]

Brain-Apparatus Communication: A Journal of Bacomics, 2022
The key to electroencephalography (EEG)-based brain-computer interface (BCI) lies in neural decoding, and its accuracy can be improved by using hybrid BCI paradigms, that is, fusing multiple paradigms.
Wen-Lin Luo, Wanguang Yin, Quanying Liu, Youzhi Qu   +3 more
semanticscholar   +1 more source