AIMC Topic: Event-Related Potentials, P300
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Latent alignment in deep learning models for EEG decoding.
Journal of neural engineering
Feb 17, 2025
. Brain-computer interfaces (BCIs) face a significant challenge due to variability in electroencephalography (EEG) signals across individuals. While recent approaches have focused on standardizing input signal distributions, we propose that aligning ...
A protocol for trustworthy EEG decoding with neural networks.
Neural networks : the official journal of the International Neural Network Society
Nov 2, 2024
Deep learning solutions have rapidly emerged for EEG decoding, achieving state-of-the-art performance on a variety of decoding tasks. Despite their high performance, existing solutions do not fully address the challenge posed by the introduction of m...
Transfer Learning With Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-Centre Data.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Oct 22, 2024
Machine learning and deep learning advancements have boosted Brain-Computer Interface (BCI) performance, but their wide-scale applicability is limited due to factors like individual health, hardware variations, and cultural differences affecting neur...
Subject-Independent Wearable P300 Brain-Computer Interface Based on Convolutional Neural Network and Metric Learning.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 25, 2024
The calibration procedure for a wearable P300 brain-computer interface (BCI) greatly impact the user experience of the system. Each user needs to spend additional time establishing a decoder adapted to their own brainwaves. Therefore, achieving subje...
Inter-participant transfer learning with attention based domain adversarial training for P300 detection.
Neural networks : the official journal of the International Neural Network Society
Aug 22, 2024
A Brain-computer interface (BCI) system establishes a novel communication channel between the human brain and a computer. Most event related potential-based BCI applications make use of decoding models, which requires training. This training process ...
Evaluating Deep Learning Performance for P300 Neural Signal Classification.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 11, 2024
P300 event-related potential (ERP) signals are useful neurological biomarkers, and their accurate classification is important when studying the cognitive functions in patients with neurological disorders. While many studies have proposed models for c...
Classification of Targets and Distractors in an Audiovisual Attention Task Based on Electroencephalography.
Sensors (Basel, Switzerland)
Dec 3, 2023
Within the broader context of improving interactions between artificial intelligence and humans, the question has arisen regarding whether auditory and rhythmic support could increase attention for visual stimuli that do not stand out clearly from an...
Ensemble Support Vector Recurrent Neural Network for Brain Signal Detection.
IEEE transactions on neural networks and learning systems
Oct 27, 2022
The brain-computer interface (BCI) P300 speller analyzes the P300 signals from the brain to achieve direct communication between humans and machines, which can assist patients with severe disabilities to control external machines or robots to complet...
Leveraging Deep Learning Techniques to Improve P300-Based Brain Computer Interfaces.
IEEE journal of biomedical and health informatics
Oct 4, 2022
Brain-Computer Interface (BCI) has become an established technology to interconnect a human brain and an external device. One of the most popular protocols for BCI is based on the extraction of the so-called P300 wave from electroencephalography (EEG...
The Effect of the Graphic Structures of Humanoid Robot on N200 and P300 Potentials.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jul 20, 2020
Humanoid robots are widely used in brain computer interface (BCI). Using a humanoid robot stimulus could increase the amplitude of event-related potentials (ERPs), which improves BCI performance. Since a humanoid robot contains many human elements, t...
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