EEG-based brain-computer interfaces: a thorough literature survey
Brain–computer interface (BCI) technology has been studied with the fundamental goal of
helping disabled people communicate with the outside world using brain signals. In …
helping disabled people communicate with the outside world using brain signals. In …
Convolutional neural network for high-accuracy functional near-infrared spectroscopy in a brain–computer interface: three-class classification of rest, right-, and left …
T Trakoolwilaiwan, B Behboodi, J Lee, K Kim… - …, 2018 - spiedigitallibrary.org
The aim of this work is to develop an effective brain–computer interface (BCI) method based
on functional near-infrared spectroscopy (fNIRS). In order to improve the performance of the …
on functional near-infrared spectroscopy (fNIRS). In order to improve the performance of the …
Optimal feature selection from fNIRS signals using genetic algorithms for BCI
In this paper, a novel technique for determination of the optimal feature combinations and,
thereby, acquisition of the maximum classification performance for a functional near-infrared …
thereby, acquisition of the maximum classification performance for a functional near-infrared …
Improving mental task classification by adding high frequency band information
L Zhang, W He, C He, P Wang - Journal of medical systems, 2010 - Springer
Features extracted from delta, theta, alpha, beta and gamma bands spanning low frequency
range are commonly used to classify scalp-recorded electroencephalogram (EEG) for …
range are commonly used to classify scalp-recorded electroencephalogram (EEG) for …
Subject-independent functional near-infrared spectroscopy-based brain–computer interfaces based on convolutional neural networks
Functional near-infrared spectroscopy (fNIRS) has attracted increasing attention in the field
of brain–computer interfaces (BCIs) owing to their advantages such as non-invasiveness …
of brain–computer interfaces (BCIs) owing to their advantages such as non-invasiveness …
[HTML][HTML] Study of electroencephalographic signal processing and classification techniques towards the use of brain-computer interfaces in virtual reality applications
F Lotte - 2008 - hal.science
A Brain-Computer Interface (BCI) is a communication system which enables its users to
send commands to a computer by using brain activity only, this brain activity being …
send commands to a computer by using brain activity only, this brain activity being …
Analysis of different classification techniques for two‐class functional near‐infrared spectroscopy‐based brain‐computer interface
We analyse and compare the classification accuracies of six different classifiers for a two‐
class mental task (mental arithmetic and rest) using functional near‐infrared spectroscopy …
class mental task (mental arithmetic and rest) using functional near‐infrared spectroscopy …
[HTML][HTML] Enhanced performance by a hybrid NIRS–EEG brain computer interface
Noninvasive Brain Computer Interfaces (BCI) have been promoted to be used for
neuroprosthetics. However, reports on applications with electroencephalography (EEG) …
neuroprosthetics. However, reports on applications with electroencephalography (EEG) …
A review of classification algorithms for EEG-based brain–computer interfaces
In this paper we review classification algorithms used to design brain–computer interface
(BCI) systems based on electroencephalography (EEG). We briefly present the commonly …
(BCI) systems based on electroencephalography (EEG). We briefly present the commonly …
EEG dataset for RSVP and P300 speller brain-computer interfaces
As attention to deep learning techniques has grown, many researchers have attempted to
develop ready-to-go brain-computer interfaces (BCIs) that include automatic processing …
develop ready-to-go brain-computer interfaces (BCIs) that include automatic processing …