AIMC Topic: Electroencephalography

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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
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...

Geometric Deep Learning for Subject Independent Epileptic Seizure Prediction Using Scalp EEG Signals.

IEEE journal of biomedical and health informatics
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...

A neuromorphic spiking neural network detects epileptic high frequency oscillations in the scalp EEG.

Scientific reports
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...

Investigating EEG-based functional connectivity patterns for multimodal emotion recognition.

Journal of neural engineering
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...

Continuous Scoring of Depression From EEG Signals via a Hybrid of Convolutional Neural Networks.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Depression score is traditionally determined by taking the Beck depression inventory (BDI) test, which is a qualitative questionnaire. Quantitative scoring of depression has also been achieved by analyzing and classifying pre-recorded electroencephal...

Propofol Anesthesia Depth Monitoring Based on Self-Attention and Residual Structure Convolutional Neural Network.

Computational and mathematical methods in medicine
METHODS: We compare nine index values, select CNN+EEG, which has good correlation with BIS index, as an anesthesia state observation index to identify the parameters of the model, and establish a model based on self-attention and dual resistructure c...

Deep-learning online EEG decoding brain-computer interface using error-related potentials recorded with a consumer-grade headset.

Biomedical physics & engineering express
Brain-computer interfaces (BCIs) allow subjects with sensorimotor disability to interact with the environment. Non-invasive BCIs relying on EEG signals such as event-related potentials (ERPs) have been established as a reliable compromise between spa...

Cross-Task Cognitive Workload Recognition Based on EEG and Domain Adaptation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Cognitive workload recognition is pivotal to maintain the operator's health and prevent accidents in the human-robot interaction condition. So far, the focus of workload research is mostly restricted to a single task, yet cross-task cognitive workloa...

A gradient-based automatic optimization CNN framework for EEG state recognition.

Journal of neural engineering
. The electroencephalogram (EEG) signal, as a data carrier that can contain a large amount of information about the human brain in different states, is one of the most widely used metrics for assessing human psychophysiological states. Among a variet...

Review on Epileptic Seizure Prediction: Machine Learning and Deep Learning Approaches.

Computational and mathematical methods in medicine
Epileptic seizures occur due to brain abnormalities that can indirectly affect patient's health. It occurs abruptly without any symptoms and thus increases the mortality rate of humans. Almost 1% of world's population suffers from epileptic seizures....