AIMC Topic: Electroencephalography

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Characterizing Brain Signals for Epileptic Pre-ictal Signal Classification.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 21, 2022
Epilepsy is a kind of neurological disorder characterized by recurrent epileptic seizures. While it is crucial to characterize pre-ictal brain electrical activities, the problem to this day still remains computationally challenging. Using brain signa...
Seizures Signal Processing, Computer-Assisted Humans Neural Networks, Computer Brain Electroencephalography Epilepsy
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An EEG Classification-Based Method for Single-Trial N170 Latency Detection and Estimation.

Computational and mathematical methods in medicine Feb 18, 2022
Event-related potentials (ERPs) can reflect the high-level thinking activities of the brain. In ERP analysis, the superposition and averaging method is often used to estimate ERPs. However, the single-trial ERP estimation can provide researchers with...
Evoked Potentials Male Humans Computational Biology Logistic Models Neural Networks, Computer Brain Female Computer Simulation Young Adult Support Vector Machine Adult Models, Neurological Electroencephalography Signal Processing, Computer-Assisted Linear Models Signal-To-Noise Ratio
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Towards a universal and privacy preserving EEG-based authentication system.

Scientific reports Feb 15, 2022
EEG-based authentication has gained much interest in recent years. However, despite its growing appeal, there are still various challenges to their practical use, such as lack of universality, lack of privacy-preserving, and lack of ease of use. In t...
Data Collection Research Design Deep Learning Electroencephalography Humans Algorithms
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Research on Emotion Recognition of EEG Signal Based on Convolutional Neural Networks and High-Order Cross-Analysis.

Journal of healthcare engineering Feb 15, 2022
Emotion recognition means the automatic identification of a human's emotional state by obtaining his/her physiological or nonphysiological signals. The EEG-based method is an effective mechanism, which is commonly used for the recognition of emotions...
Male Emotions Electroencephalography Neural Networks, Computer Humans Databases, Factual Female
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Epileptic Seizure Detection with Hybrid Time-Frequency EEG Input: A Deep Learning Approach.

Computational and mathematical methods in medicine Feb 15, 2022
The precise detection of epileptic seizure helps to prevent the serious consequences of seizures. As the electroencephalogram (EEG) reflects the brain activity of patients effectively, it has been widely used in epileptic seizure detection in the pas...
Humans Seizures Neural Networks, Computer Signal Processing, Computer-Assisted Algorithms Wavelet Analysis Computational Biology Databases, Factual Fourier Analysis Electroencephalography Diagnosis, Computer-Assisted Epilepsy Deep Learning
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Automated detection of clinical depression based on convolution neural network model.

Biomedizinische Technik. Biomedical engineering Feb 10, 2022
As a common mental disorder, depression is placing an increasing burden on families and society. However, the current methods of depression detection have some limitations, and it is essential to find an objective and efficient method. With the devel...
Humans Neural Networks, Computer Electroencephalography Artificial Intelligence Algorithms Depression
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Scalp EEG-Based Pain Detection Using Convolutional Neural Network.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Feb 9, 2022
Pain is an integrative phenomenon coupled with dynamic interactions between sensory and contextual processes in the brain, often associated with detectable neurophysiological changes. Recent advances in brain activity recording tools and machine lear...
Machine Learning Electroencephalography Pain Scalp Humans Neural Networks, Computer
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Geometric Deep Learning for Subject Independent Epileptic Seizure Prediction Using Scalp EEG Signals.

IEEE journal of biomedical and health informatics Feb 4, 2022
Recently, researchers in the biomedical community have introduced deep learning-based epileptic seizure prediction models using electroencephalograms (EEGs) that can anticipate an epileptic seizure by differentiating between the pre-ictal and interic...
Electroencephalography Humans Seizures Scalp Algorithms Deep Learning
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A neuromorphic spiking neural network detects epileptic high frequency oscillations in the scalp EEG.

Scientific reports Feb 2, 2022
Interictal High Frequency Oscillations (HFO) are measurable in scalp EEG. This development has aroused interest in investigating their potential as biomarkers of epileptogenesis, seizure propensity, disease severity, and treatment response. The deman...
Humans Neural Networks, Computer Brain Waves Drug Resistant Epilepsy Epilepsies, Partial Wearable Electronic Devices Electroencephalography Time Factors Signal Processing, Computer-Assisted Child, Preschool Artifacts Male Child Brain Treatment Outcome Infant Female Predictive Value of Tests Adolescent Reproducibility of Results
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Investigating EEG-based functional connectivity patterns for multimodal emotion recognition.

Journal of neural engineering Jan 31, 2022
Previous studies on emotion recognition from electroencephalography (EEG) mainly rely on single-channel-based feature extraction methods, which ignore the functional connectivity between brain regions. Hence, in this paper, we propose a novel emotion...
Arousal Emotions Electroencephalography Neural Networks, Computer Brain
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