AIMC Topic: Electroencephalography

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A fine-tuning deep residual convolutional neural network for emotion recognition based on frequency-channel matrices representation of one-dimensional electroencephalography.

Computer methods in biomechanics and biomedical engineering Nov 28, 2023
Emotion recognition (ER) plays a crucial role in enabling machines to perceive human emotional and psychological states, thus enhancing human-machine interaction. Recently, there has been a growing interest in ER based on electroencephalogram (EEG) s...
Neural Networks, Computer Deep Learning Convolutional Neural Networks Emotions Humans Electroencephalography Signal Processing, Computer-Assisted
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Learning Curve in Robotic Stereoelectroencephalography: Single Platform Experience.

World neurosurgery Nov 28, 2023
BACKGROUND: Learning curve, training, and cost impede widespread implementation of new technology. Neurosurgical robotic technology introduces challenges to visuospatial reasoning and requires the acquisition of new fine motor skills. Studies detaili...
Learning Curve Drug Resistant Epilepsy Electrodes, Implanted Robotic Surgical Procedures Retrospective Studies Humans Robotics Stereotaxic Techniques Child Electroencephalography
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An Effective Hybrid Deep Learning Model for Single-Channel EEG-Based Subject-Independent Drowsiness Recognition.

Brain topography Nov 23, 2023
Nowadays, road accidents pose a severe risk in cases of sleep disorders. We proposed a novel hybrid deep-learning model for detecting drowsiness to address this issue. The proposed model combines the strengths of discrete wavelet long short-term memo...
Electroencephalography Benchmarking Mental Recall Recognition, Psychology Humans Deep Learning
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EESCN: A novel spiking neural network method for EEG-based emotion recognition.

Computer methods and programs in biomedicine Nov 20, 2023
BACKGROUND AND OBJECTIVE: Although existing artificial neural networks have achieved good results in electroencephalograph (EEG) emotion recognition, further improvements are needed in terms of bio-interpretability and robustness. In this research, w...
Emotions Neural Networks, Computer Electroencephalography
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Spatio-Temporal Explanation of 3D-EEGNet for Motor Imagery EEG Classification Using Permutation and Saliency.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Nov 16, 2023
Recently, convolutional neural network (CNN)-based classification models have shown good performance for motor imagery (MI) brain-computer interfaces (BCI) using electroencephalogram (EEG) in end-to-end learning. Although a few explainable artificial...
Imagination Algorithms Neural Networks, Computer Electroencephalography Learning Humans Artificial Intelligence Brain-Computer Interfaces
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An Efficient Group Federated Learning Framework for Large-Scale EEG-Based Driver Drowsiness Detection.

International journal of neural systems Nov 15, 2023
To avoid traffic accidents, monitoring the driver's electroencephalogram (EEG) signals to assess drowsiness is an effective solution. However, aggregating the personal data of these drivers may lead to insufficient data usage and pose a risk of priva...
Area Under Curve Electroencephalography Humans Neural Networks, Computer
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Diagnostic deep learning algorithms that use resting EEG to distinguish major depressive disorder, bipolar disorder, and schizophrenia from each other and from healthy volunteers.

Journal of affective disorders Nov 12, 2023
BACKGROUND: Mood disorders and schizophrenia affect millions worldwide. Currently, diagnosis is primarily determined by reported symptomatology. As symptoms may overlap, misdiagnosis is common, potentially leading to ineffective or destabilizing trea...
Deep Learning Bipolar Disorder Humans Depressive Disorder, Major Healthy Volunteers Electroencephalography Schizophrenia
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Space-CNN: a decision classification method based on EEG signals from different brain regions.

Medical & biological engineering & computing Nov 12, 2023
Decision-making plays a critical role in an individual's interpersonal interactions and cognitive processes. Due to the issue of strong subjectivity in the classification research of art design decisions, we utilize the relatively objective electroen...
Neural Networks, Computer Algorithms Brain Wavelet Analysis Electroencephalography Humans Occipital Lobe
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Miner Fatigue Detection from Electroencephalogram-Based Relative Power Spectral Topography Using Convolutional Neural Network.

Sensors (Basel, Switzerland) Nov 9, 2023
Fatigue of miners is caused by intensive workloads, long working hours, and shift-work schedules. It is one of the major factors increasing the risk of safety problems and work mistakes. Examining the detection of miner fatigue is important because i...
Electroencephalography Neural Networks, Computer Workload Machine Learning Coal
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Hybrid optimization assisted channel selection of EEG for deep learning model-based classification of motor imagery task.

Biomedizinische Technik. Biomedical engineering Nov 8, 2023
OBJECTIVES: To design and develop an approach named HC + SMA-SSA scheme for classifying motor imagery task.
Algorithms Deep Learning Brain-Computer Interfaces Imagination Electroencephalography Signal Processing, Computer-Assisted
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