AIMC Topic: Electroencephalography
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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
Jan 31, 2022
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
Jan 29, 2022
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
Jan 28, 2022
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
Jan 28, 2022
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
Jan 24, 2022
. 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
Jan 20, 2022
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....
WeDea: A New EEG-Based Framework for Emotion Recognition.
IEEE journal of biomedical and health informatics
Jan 17, 2022
With the development of sensing technologies and machine learning, techniques that can identify emotions and inner states of a human through physiological signals, known as electroencephalography (EEG), have been actively developed and applied to var...
Electroclinical spectrum of generalized paroxysmal fast activity in adults without epileptic encephalopathy.
Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Jan 16, 2022
INTRODUCTION: Generalized paroxysmal fast activity (GPFA) is a rare and underreported EEG pattern known to be related to epileptic encephalopathy. We aimed to investigate the electroclinical spectrum of GPFA along with other atypical EEG features in ...
Enhanced Recognition of Amputated Wrist and Hand Movements by Deep Learning Method Using Multimodal Fusion of Electromyography and Electroencephalography.
Sensors (Basel, Switzerland)
Jan 16, 2022
Motion classification can be performed using biometric signals recorded by electroencephalography (EEG) or electromyography (EMG) with noninvasive surface electrodes for the control of prosthetic arms. However, current single-modal EEG and EMG based ...
Deep learning of early brain imaging to predict post-arrest electroencephalography.
Resuscitation
Jan 15, 2022
INTRODUCTION: Guidelines recommend use of computerized tomography (CT) and electroencephalography (EEG) in post-arrest prognostication. Strong associations between CT and EEG might obviate the need to acquire both modalities. We quantified these asso...
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