A comprehensive review of deep learning power in steady-state visual evoked potentials

ZT Al-Qaysi, AS Albahri, MA Ahmed, RA Hamid… - Neural Computing and …, 2024 - Springer
Brain–computer interfacing (BCI) research, fueled by deep learning, integrates insights from
diverse domains. A notable focus is on steady-state visual evoked potential (SSVEP) in BCI …

Fatigue factors and fatigue indices in SSVEP-based brain-computer interfaces: a systematic review and meta-analysis

M Azadi Moghadam, A Maleki - Frontiers in Human Neuroscience, 2023 - frontiersin.org
Background Fatigue is a serious challenge when applying a steady-state visual evoked
potential (SSVEP)-based brain-computer interfaces (BCIs) in the real world. Many …

OS-SSVEP: one-shot SSVEP classification

Y Deng, Z Ji, Y Wang, SK Zhou - Neural Networks, 2024 - Elsevier
It is extremely challenging to classify steady-state visual evoked potentials (SSVEPs) in
scenarios characterized by a huge scarcity of calibration data where only one calibration …

An improved SSVEP-based brain-computer interface with low-contrast visual stimulation and its application in UAV control

Y Cheng, L Yan, MU Shoukat, J She… - Journal of …, 2024 - journals.physiology.org
Efficient communication and regulation are crucial for advancing brain-computer interfaces
(BCIs), with the steady-state visual-evoked potential (SSVEP) paradigm demonstrating high …

Enhancing the performance of SSVEP-based BCIs by combining task-related component analysis and deep neural network

Q Wei, C Li, Y Wang, X Gao - Scientific Reports, 2025 - nature.com
Abstract Steady-State Visually Evoked Potential (SSVEP) signals can be decoded by either
a traditional machine learning algorithm or a deep learning network. Combining the two …

Enhancing SSVEP-Based BCI Performance via Consensus Information Transfer Among Subjects

X Zhang, W Wei, S Qiu, X Li, Y Wang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The brain–computer interface (BCI) based on steady-state visual evoked potential (SSVEP)
has received considerable attention for its high communication speed. While large datasets …

Ensemble strategies exploration for the calibration data optimized spatial filters based SSVEP recognition algorithms

T Luo, S Angadi, MA Elashiri - Biomedical Signal Processing and Control, 2025 - Elsevier
Steady-state visual evoked potential (SSVEP) based brain-computer interfaces (BCIs)
exhibit high information transfer rate (ITR) characteristics. However, the …

Enhancing SSVEP-BCI Performance under Fatigue State Using Dynamic Stopping Strategy

Y Han, Y Ke, R Wang, T Wang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) have
emerged as a prominent technology due to their high information transfer rate, rapid …

Enhancing detection of SSVEP-based BCIs via a novel temporally local canonical correlation analysis

G Xia, L Wang, S Xiong, J Deng - Journal of Neuroscience Methods, 2025 - Elsevier
Background In recent years, spatial filter-based frequency recognition methods have
become popular in steady-state visual evoked potential (SSVEP)-based brain-computer …

A Comparative Review of Detection Methods in SSVEP-based Brain-Computer Interfaces

A Besharat, N Samadzadehaghdam, R Afghan - IEEE Access, 2024 - ieeexplore.ieee.org
Steady-state visually evoked potential (SSVEP) refers to the brain's response to visual
stimuli at different frequencies and is widely used in brain-computer interfaces (BCIs) …