Review of Riemannian distances and divergences, applied to SSVEP-based BCI
The firstgeneration of brain-computer interfaces (BCI) classifies multi-channel
electroencephalographic (EEG) signals, enhanced by optimized spatial filters. The second …
electroencephalographic (EEG) signals, enhanced by optimized spatial filters. The second …
A graph-based hierarchical attention model for movement intention detection from EEG signals
An EEG-based Brain-Computer Interface (BCI) is a system that enables a user to
communicate with and intuitively control external devices solely using the user's intentions …
communicate with and intuitively control external devices solely using the user's intentions …
Analysis of relation between brainwave activity and reaction time of short-haul pilots based on EEG Data
The purpose of this research is to examine and assess the relation between a pilot's
concentration and reaction time with specific brain activity during short-haul flights …
concentration and reaction time with specific brain activity during short-haul flights …
Evaluation of Motor Imagery-Based BCI methods in neurorehabilitation of Parkinson's Disease patients
The study reports the performance of Parkinson's disease (PD) patients to operate Motor-
Imagery based Brain-Computer Interface (MI-BCI) and compares three selected pre …
Imagery based Brain-Computer Interface (MI-BCI) and compares three selected pre …
An EEG-based asynchronous MI-BCI system to reduce false positives with a small number of channels for neurorehabilitation: A pilot study
Many studies have used motor imagery-based brain–computer interface (MI-BCI) systems
for stroke rehabilitation to induce brain plasticity. However, they mainly focused on detecting …
for stroke rehabilitation to induce brain plasticity. However, they mainly focused on detecting …
Performance of EEG Motor-Imagery based spatial filtering methods: A BCI study on Stroke patients
A Miladinović, M Ajčević, J Jarmolowska… - Procedia Computer …, 2020 - Elsevier
The study reports the performance of stroke patients to operate Motor-Imagery based Brain-
Computer Interface (MI-BCI) in early post-stroke neurorehabilitation and compares three …
Computer Interface (MI-BCI) in early post-stroke neurorehabilitation and compares three …
Regularized partial least square regression for continuous decoding in brain-computer interfaces
Continuous decoding is a crucial step in many types of brain-computer interfaces (BCIs).
Linear regression techniques have been widely used to determine a linear relation between …
Linear regression techniques have been widely used to determine a linear relation between …
Estimating person-specific neural correlates of mental rotation: A machine learning approach
S Uslu, M Tangermann, C Vögele - Plos one, 2024 - journals.plos.org
Using neurophysiological measures to model how the brain performs complex cognitive
tasks such as mental rotation is a promising way towards precise predictions of behavioural …
tasks such as mental rotation is a promising way towards precise predictions of behavioural …
[PDF][PDF] Odor and Subject Identification Using Electroencephalography Reaction to Olfactory.
O Aydemir - Traitement du Signal, 2020 - researchgate.net
Accepted: 16 September 2020 It is certain that the human brain responds to all kinds of
inputs such as feeling, sound, light, and odor. However, to the best of our knowledge, limited …
inputs such as feeling, sound, light, and odor. However, to the best of our knowledge, limited …
Pilot study on using Hybrid–Cascade filtering on brain signals for the control purposes
M Pelc, D Mikołajewski… - … on Methods and …, 2023 - ieeexplore.ieee.org
We present an initial study conducted on fNIRS signals using Hybrid-Cascade filters for the
purpose of their quality improvement. Whilst many studies focus on filtering brain signals, so …
purpose of their quality improvement. Whilst many studies focus on filtering brain signals, so …