AIMC Topic: Electroencephalography

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

Neurobiology of aging May 4, 2021
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...
Aged, 80 and over Male Cohort Studies Female Aged Follow-Up Studies Magnetic Resonance Imaging Electroencephalography Genotype Mass Screening Machine Learning Biomarkers Humans Apolipoprotein E4 Nerve Degeneration Hippocampus Neuropsychological Tests Alzheimer Disease Positron-Emission Tomography
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Neuromagnetic high frequency spikes are a new and noninvasive biomarker for localization of epileptogenic zones.

Seizure May 4, 2021
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...
Humans Artificial Intelligence Electroencephalography Drug Resistant Epilepsy Magnetoencephalography Biomarkers Child
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The Function of Color and Structure Based on EEG Features in Landscape Recognition.

International journal of environmental research and public health May 3, 2021
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...
Gamma Rhythm Electroencephalography Recognition, Psychology Algorithms Support Vector Machine Humans
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Interpreting deep learning models for epileptic seizure detection on EEG signals.

Artificial intelligence in medicine May 1, 2021
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 ...
Seizures Signal Processing, Computer-Assisted Electroencephalography Epilepsy Neural Networks, Computer Deep Learning Humans
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Probabilistic learning vector quantization on manifold of symmetric positive definite matrices.

Neural networks : the official journal of the International Neural Network Society Apr 28, 2021
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...
Electroencephalography Machine Learning Algorithms
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Detection of Negative Stress through Spectral Features of Electroencephalographic Recordings and a Convolutional Neural Network.

Sensors (Basel, Switzerland) Apr 27, 2021
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...
Brain Emotions Neural Networks, Computer Electroencephalography Algorithms
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Edge deep learning for neural implants: a case study of seizure detection and prediction.

Journal of neural engineering Apr 26, 2021
Implanted devices providing real-time neural activity classification and control are increasingly used to treat neurological disorders, such as epilepsy and Parkinson's disease. Classification performance is critical to identifying brain states appro...
Algorithms Deep Learning Seizures Electroencephalography Humans Neural Networks, Computer
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Automated EEG pathology detection based on different convolutional neural network models: Deep learning approach.

Computers in biology and medicine Apr 25, 2021
The brain electrical activity, recorded and materialized as electroencephalogram (EEG) signals, is known to be very useful in the diagnosis of brain-related pathology. However, manual examination of these EEG signals has various limitations, includin...
Electroencephalography Head Neural Networks, Computer Deep Learning Support Vector Machine Humans
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Diagnosis of Alzheimer's Disease by Time-Dependent Power Spectrum Descriptors and Convolutional Neural Network Using EEG Signal.

Computational and mathematical methods in medicine Apr 23, 2021
Using strategies that obtain biomarkers where early symptoms coincide, the early detection of Alzheimer's disease and its complications is essential. Electroencephalogram is a technology that allows thousands of neurons with equal spatial orientation...
Early Diagnosis Signal Processing, Computer-Assisted Alzheimer Disease Cognitive Dysfunction Case-Control Studies Support Vector Machine Discriminant Analysis Computational Biology Humans Diagnosis, Computer-Assisted Electroencephalography Neural Networks, Computer
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Does agency matter? Neural processing of robotic movements in 4- and 8-year olds.

Neuropsychologia Apr 21, 2021
Despite the increase in interactions between children and robots, our understanding of children's neural processing of robotic movements is limited. The current study theorized that motor resonance hinges on the agency of an actor: its ability to per...
Cross-Sectional Studies Robotics Movement Electroencephalography Robotic Surgical Procedures
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