AIMC Topic: Electroencephalography

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Activation patterns of interictal epileptiform discharges in relation to sleep and seizures: An artificial intelligence driven data analysis.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: To quantify effects of sleep and seizures on the rate of interictal epileptiform discharges (IED) and to classify patients with epilepsy based on IED activation patterns.

Automated accurate emotion recognition system using rhythm-specific deep convolutional neural network technique with multi-channel EEG signals.

Computers in biology and medicine
Emotion is interpreted as a psycho-physiological process, and it is associated with personality, behavior, motivation, and character of a person. The objective of affective computing is to recognize different types of emotions for human-computer inte...

Machine learning of EEG spectra classifies unconsciousness during GABAergic anesthesia.

PloS one
In current anesthesiology practice, anesthesiologists infer the state of unconsciousness without directly monitoring the brain. Drug- and patient-specific electroencephalographic (EEG) signatures of anesthesia-induced unconsciousness have been identi...

An Attention-Based Deep Learning Approach for Sleep Stage Classification With Single-Channel EEG.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Automatic sleep stage mymargin classification is of great importance to measure sleep quality. In this paper, we propose a novel attention-based deep learning architecture called AttnSleep to classify sleep stages using single channel EEG signals. Th...

A machine learning approach to screen for preclinical Alzheimer's disease.

Neurobiology of aging
Combining multimodal biomarkers could help in the early diagnosis of Alzheimer's disease (AD). We included 304 cognitively normal individuals from the INSIGHT-preAD cohort. Amyloid and neurodegeneration were assessed on F-florbetapir and F-fluorodeox...

Neuromagnetic high frequency spikes are a new and noninvasive biomarker for localization of epileptogenic zones.

Seizure
OBJECTIVE: One barrier hindering high frequency brain signals (HFBS, >80 Hz) from wide clinical applications is that the brain generates both pathological and physiological HFBS. This study was to find specific biomarkers for localizing epileptogenic...

The Function of Color and Structure Based on EEG Features in Landscape Recognition.

International journal of environmental research and public health
Both color and structure make important contributions to human visual perception, as well as the evaluation of landscape quality and landscape aesthetics. The EEG equipment liveamp32 was used to record the EEG signals of humans when viewing landscape...

Interpreting deep learning models for epileptic seizure detection on EEG signals.

Artificial intelligence in medicine
While Deep Learning (DL) is often considered the state-of-the art for Artificial Intel-ligence-based medical decision support, it remains sparsely implemented in clinical practice and poorly trusted by clinicians due to insufficient interpretability ...

Probabilistic learning vector quantization on manifold of symmetric positive definite matrices.

Neural networks : the official journal of the International Neural Network Society
In this paper, we develop a new classification method for manifold-valued data in the framework of probabilistic learning vector quantization. In many classification scenarios, the data can be naturally represented by symmetric positive definite matr...

Detection of Negative Stress through Spectral Features of Electroencephalographic Recordings and a Convolutional Neural Network.

Sensors (Basel, Switzerland)
In recent years, electroencephalographic (EEG) signals have been intensively used in the area of emotion recognition, partcularly in distress identification due to its negative impact on physical and mental health. Traditionally, brain activity has b...