AIMC Topic: Electroencephalography

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A systematic evaluation of Euclidean alignment with deep learning for EEG decoding.

Journal of neural engineering Jun 11, 2024
Electroencephalography signals are frequently used for various Brain-Computer interface (BCI) tasks. While deep learning (DL) techniques have shown promising results, they are hindered by the substantial data requirements. By leveraging data from mul...
Female Adult Male Deep Learning Electroencephalography Brain-Computer Interfaces Humans Algorithms
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Epilepsy detection based on multi-head self-attention mechanism.

PloS one Jun 11, 2024
CNN has demonstrated remarkable performance in EEG signal detection, yet it still faces limitations in terms of global perception. Additionally, due to individual differences in EEG signals, the generalization ability of epilepsy detection models is ...
Algorithms Signal Processing, Computer-Assisted Humans Electroencephalography Neural Networks, Computer Fourier Analysis Epilepsy
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Machine Learning in Electroconvulsive Therapy: A Systematic Review.

The journal of ECT Jun 10, 2024
Despite years of research, we are still not able to reliably predict who might benefit from electroconvulsive therapy (ECT) treatment. As we exhaust what is possible using traditional statistical analysis, ECT remains a good candidate for machine lea...
Machine Learning Humans Electroencephalography Brain Treatment Outcome Electroconvulsive Therapy
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An end-to-end multi-task motor imagery EEG classification neural network based on dynamic fusion of spectral-temporal features.

Computers in biology and medicine Jun 8, 2024
Electroencephalograph (EEG) brain-computer interfaces (BCI) have potential to provide new paradigms for controlling computers and devices. The accuracy of brain pattern classification in EEG BCI is directly affected by the quality of features extract...
Signal Processing, Computer-Assisted Brain-Computer Interfaces Imagination Brain Electroencephalography Humans Neural Networks, Computer
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Multimodal fusion for anticipating human decision performance.

Scientific reports Jun 8, 2024
Anticipating human decisions while performing complex tasks remains a formidable challenge. This study proposes a multimodal machine-learning approach that leverages image features and electroencephalography (EEG) data to predict human response corre...
Male Decision Making Electroencephalography Female Young Adult Adult Machine Learning Algorithms Humans
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A Dynamic Window Method Based on Reinforcement Learning for SSVEP Recognition.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jun 7, 2024
Steady-state visual evoked potential (SSVEP) is one of the most used brain-computer interface (BCI) paradigms. Conventional methods analyze SSVEPs at a fixed window length. Compared with these methods, dynamic window methods can achieve a higher info...
Male Reinforcement, Psychology Female Humans Bayes Theorem Electroencephalography Young Adult Neural Networks, Computer Discriminant Analysis Brain-Computer Interfaces Adult Machine Learning Evoked Potentials, Visual Algorithms
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A Multi-Level Interpretable Sleep Stage Scoring System by Infusing Experts' Knowledge Into a Deep Network Architecture.

IEEE transactions on pattern analysis and machine intelligence Jun 5, 2024
In recent years, deep learning has shown potential and efficiency in a wide area including computer vision, image and signal processing. Yet, translational challenges remain for user applications due to a lack of interpretability of algorithmic decis...
Female Young Adult Adult Humans Neural Networks, Computer Algorithms Signal Processing, Computer-Assisted Polysomnography Sleep Stages Male Deep Learning Electroencephalography
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Deep learning classification of EEG-based BCI monitoring of the attempted arm and hand movements.

Biomedizinische Technik. Biomedical engineering Jun 4, 2024
OBJECTIVES: The primary objective of this research is to improve the average classification performance for specific movements in patients with cervical spinal cord injury (SCI).
Arm Brain-Computer Interfaces Spinal Cord Injuries Deep Learning Electroencephalography Hand Movement Humans Neural Networks, Computer Reproducibility of Results
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Optimizing motor imagery BCI models with hard trials removal and model refinement.

Biomedical physics & engineering express Jun 4, 2024
Deep learning models have demonstrated remarkable performance in the classification of motor imagery BCI systems. However, these models exhibit sensitivity to challenging trials, often called hard trials, leading to performance degradation. In this p...
Artificial Intelligence Algorithms Deep Learning Humans Neural Networks, Computer Imagination Electroencephalography Brain-Computer Interfaces
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An Automatic Lie Detection Model Using EEG Signals Based on the Combination of Type 2 Fuzzy Sets and Deep Graph Convolutional Networks.

Sensors (Basel, Switzerland) Jun 3, 2024
In recent decades, many different governmental and nongovernmental organizations have used lie detection for various purposes, including ensuring the honesty of criminal confessions. As a result, this diagnosis is evaluated with a polygraph machine. ...
Humans Neural Networks, Computer Algorithms Female Young Adult Adult Electroencephalography Male Signal Processing, Computer-Assisted Fuzzy Logic Lie Detection
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