Consumer grade EEG measuring sensors as research tools: A review
P Sawangjai, S Hompoonsup… - IEEE Sensors …, 2019 - ieeexplore.ieee.org
Since the launch of the first consumer grade EEG measuring sensorsNeuroSky Mindset'in
2007, the market has witnessed an introduction of at least one new product every year by …
2007, the market has witnessed an introduction of at least one new product every year by …
Steady-state visually evoked potentials: focus on essential paradigms and future perspectives
After 40 years of investigation, steady-state visually evoked potentials (SSVEPs) have been
shown to be useful for many paradigms in cognitive (visual attention, binocular rivalry …
shown to be useful for many paradigms in cognitive (visual attention, binocular rivalry …
Improving the performance of individually calibrated SSVEP-BCI by task-discriminant component analysis
A brain-computer interface (BCI) provides a direct communication channel between a brain
and an external device. Steady-state visual evoked potential based BCI (SSVEP-BCI) has …
and an external device. Steady-state visual evoked potential based BCI (SSVEP-BCI) has …
Robust similarity measurement based on a novel time filter for SSVEPs detection
The steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) has
received extensive attention in research for the less training time, excellent recognition …
received extensive attention in research for the less training time, excellent recognition …
Sparse Bayesian learning for end-to-end EEG decoding
Decoding brain activity from non-invasive electroencephalography (EEG) is crucial for brain-
computer interfaces (BCIs) and the study of brain disorders. Notably, end-to-end EEG …
computer interfaces (BCIs) and the study of brain disorders. Notably, end-to-end EEG …
[HTML][HTML] A convolutional neural network for steady state visual evoked potential classification under ambulatory environment
The robust analysis of neural signals is a challenging problem. Here, we contribute a
convolutional neural network (CNN) for the robust classification of a steady-state visual …
convolutional neural network (CNN) for the robust classification of a steady-state visual …
Implementing over 100 command codes for a high-speed hybrid brain-computer interface using concurrent P300 and SSVEP features
Objective: Recently, electroencephalography (EEG)-based brain-computer interfaces (BCIs)
have made tremendous progress in increasing communication speed. However, current BCI …
have made tremendous progress in increasing communication speed. However, current BCI …
EEG-based cross-subject driver drowsiness recognition with an interpretable convolutional neural network
In the context of electroencephalogram (EEG)-based driver drowsiness recognition, it is still
challenging to design a calibration-free system, since EEG signals vary significantly among …
challenging to design a calibration-free system, since EEG signals vary significantly among …
A survey on canonical correlation analysis
In recent years, the advances in data collection and statistical analysis promotes canonical
correlation analysis (CCA) available for more advanced research. CCA is the main …
correlation analysis (CCA) available for more advanced research. CCA is the main …
Frequency recognition in SSVEP-based BCI using multiset canonical correlation analysis
Canonical correlation analysis (CCA) has been one of the most popular methods for
frequency recognition in steady-state visual evoked potential (SSVEP)-based brain …
frequency recognition in steady-state visual evoked potential (SSVEP)-based brain …