AIMC Topic: Electroencephalography

Clear Filters Showing 211 to 220 of 2115 articles

Interpretable Multi-Branch Architecture for Spatiotemporal Neural Networks and Its Application in Seizure Prediction.

IEEE journal of biomedical and health informatics Jan 7, 2025
Currently, spatiotemporal convolutional neural networks (CNNs) for electroencephalogram (EEG) signals have emerged as promising tools for seizure prediction (SP), which explore the spatiotemporal biomarkers in an epileptic brain. Generally, these CNN...
Humans Neural Networks, Computer Brain Signal Processing, Computer-Assisted Male Electroencephalography Seizures Female Young Adult Adult
View on PubMed DOI

Multiscale Spatial-Temporal Feature Fusion Neural Network for Motor Imagery Brain-Computer Interfaces.

IEEE journal of biomedical and health informatics Jan 7, 2025
Motor imagery, one of the main brain-computer interface (BCI) paradigms, has been extensively utilized in numerous BCI applications, such as the interaction between disabled people and external devices. Precise decoding, one of the most significant a...
Male Brain-Computer Interfaces Humans Female Imagination Electroencephalography Neural Networks, Computer Signal Processing, Computer-Assisted Young Adult Adult
View on PubMed DOI

MFRC-Net: Multi-Scale Feature Residual Convolutional Neural Network for Motor Imagery Decoding.

IEEE journal of biomedical and health informatics Jan 7, 2025
Motor imagery (MI) decoding is the basis of external device control via electroencephalogram (EEG). However, the majority of studies prioritize enhancing the accuracy of decoding methods, often overlooking the magnitude and computational resource dem...
Humans Neural Networks, Computer Convolutional Neural Networks Electroencephalography Signal Processing, Computer-Assisted Brain-Computer Interfaces Imagination
View on PubMed DOI

An EEG-based emotion recognition method by fusing multi-frequency-spatial features under multi-frequency bands.

Journal of neuroscience methods Jan 6, 2025
BACKGROUND: Recognition of emotion changes is of great significance to a person's physical and mental health. At present, EEG-based emotion recognition methods are mainly focused on time or frequency domains, but rarely on spatial information. Theref...
Adult Recognition, Psychology Male Humans Brain Brain Mapping Emotions Neural Networks, Computer Female Electroencephalography Young Adult Signal Processing, Computer-Assisted
View on PubMed DOI

A hybrid CNN-Bi-LSTM model with feature fusion for accurate epilepsy seizure detection.

BMC medical informatics and decision making Jan 6, 2025
BACKGROUND: The diagnosis and treatment of epilepsy continue to face numerous challenges, highlighting the urgent need for the development of rapid, accurate, and non-invasive methods for seizure detection. In recent years, advancements in the analys...
Epilepsy Seizures Wavelet Analysis Deep Learning Support Vector Machine Humans Electroencephalography Neural Networks, Computer
View on PubMed DOI

EEG Signals Classification Related to Visual Objects Using Long Short-Term Memory Network and Nonlinear Interval Type-2 Fuzzy Regression.

Brain topography Jan 6, 2025
By gaining insights into how brain activity is encoded and decoded, we enhance our understanding of brain function. This study introduces a method for classifying EEG signals related to visual objects, employing a combination of an LSTM network and n...
Humans Neural Networks, Computer Brain Female Signal Processing, Computer-Assisted Male Young Adult Nonlinear Dynamics Fuzzy Logic Adult Electroencephalography
View on PubMed DOI

A hybrid network using transformer with modified locally linear embedding and sliding window convolution for EEG decoding.

Journal of neural engineering Jan 6, 2025
. Brain-computer interface(BCI) is leveraged by artificial intelligence in EEG signal decoding, which makes it possible to become a new means of human-machine interaction. However, the performance of current EEG decoding methods is still insufficient...
Algorithms Electroencephalography Signal Processing, Computer-Assisted Humans Neural Networks, Computer Linear Models Brain-Computer Interfaces Imagination
View on PubMed DOI

Cognitive load detection through EEG lead wise feature optimization and ensemble classification.

Scientific reports Jan 4, 2025
Cognitive load stimulates neural activity, essential for understanding the brain's response to stress-inducing stimuli or mental strain. This study examines the feasibility of evaluating cognitive load by extracting, selection, and classifying featur...
Electroencephalography Signal Processing, Computer-Assisted Male Cognition Machine Learning Female Humans Algorithms Young Adult Brain Adult
View on PubMed DOI

DHCT-GAN: Improving EEG Signal Quality with a Dual-Branch Hybrid CNN-Transformer Network.

Sensors (Basel, Switzerland) Jan 3, 2025
Electroencephalogram (EEG) signals are important bioelectrical signals widely used in brain activity studies, cognitive mechanism research, and the diagnosis and treatment of neurological disorders. However, EEG signals are often influenced by variou...
Electroencephalography Algorithms Humans Signal-To-Noise Ratio Signal Processing, Computer-Assisted Brain Neural Networks, Computer Artifacts Deep Learning
View on PubMed DOI

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

Scientific reports Jan 2, 2025
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 methods is expected to enhance the performance of an SSVEP-based brain-computer int...
Evoked Potentials, Visual Neural Networks, Computer Algorithms Deep Learning Electroencephalography Signal Processing, Computer-Assisted Brain-Computer Interfaces Humans
View on PubMed DOI
Popular Topics
Recent Journals