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 …
[HTML][HTML] Wireless sensors for brain activity—a survey
Over the last decade, the area of electroencephalography (EEG) witnessed a progressive
move from high-end large measurement devices, relying on accurate construction and …
move from high-end large measurement devices, relying on accurate construction and …
[HTML][HTML] Characterization of industry 4.0 lean management problem-solving behavioral patterns using EEG sensors and deep learning
Industry 4.0 leaders solve problems all of the time. Successful problem-solving behavioral
pattern choice determines organizational and personal success, therefore a proper …
pattern choice determines organizational and personal success, therefore a proper …
[HTML][HTML] Measuring the non-linear directed information flow in schizophrenia by multivariate transfer entropy
People living with schizophrenia (SCZ) experience severe brain network deterioration. The
brain is constantly fizzling with non-linear causal activities measured by …
brain is constantly fizzling with non-linear causal activities measured by …
An interpretable convolutional neural network for P300 detection: Analysis of time frequency features for limited data
In this study, a new deep learning-based methodology is developed for P300 detection in
brain computer interface (BCI) systems based on time-frequency (TF) features of EEG …
brain computer interface (BCI) systems based on time-frequency (TF) features of EEG …
10 years of EPOC: A scoping review of Emotiv's portable EEG device
BACKGROUND Commercially-made low-cost electroencephalography (EEG) devices have
become increasingly available over the last decade. One of these devices, Emotiv EPOC, is …
become increasingly available over the last decade. One of these devices, Emotiv EPOC, is …
Fractional S-transform and its properties: a comprehensive survey
In time–frequency analysis, generalization of S-transform (ST) is known as fractional S-
transform. Recently, fractional S-transform (FrST) has played an important role in the area of …
transform. Recently, fractional S-transform (FrST) has played an important role in the area of …
P300 based character recognition using sparse autoencoder with ensemble of SVMs
In this study, a brain–computer interface (BCI) system known as P300 speller is used to spell
the word or character without any muscle activity. For P300 signal classification, feature …
the word or character without any muscle activity. For P300 signal classification, feature …
A comparative study of wavelet families for electromyography signal classification based on discrete wavelet transform
A Achmamad, A Jbari - Bulletin of Electrical Engineering and Informatics, 2020 - beei.org
Automatic detection of neuromuscular disorders performed using electromyography (EMG)
has become an interesting domain for many researchers. In this paper, we present an …
has become an interesting domain for many researchers. In this paper, we present an …
A noise-robust sparse approach to the time-frequency representation of visual evoked potentials
P Sheela, SD Puthankattil - Computers in Biology and Medicine, 2021 - Elsevier
Background Visual evoked potential (VEP) offers a promising research strategy in the effort
to characterise brain disorders. Pertinent signal processing techniques enable the …
to characterise brain disorders. Pertinent signal processing techniques enable the …