AIMC Topic: Electroencephalography
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An Integrated Electroencephalography and Eye-Tracking Analysis Using eXtreme Gradient Boosting for Mental Workload Evaluation in Surgery.
Human factors
May 1, 2025
ObjectiveWe aimed to develop advanced machine learning models using electroencephalogram (EEG) and eye-tracking data to predict the mental workload associated with engaging in various surgical tasks.BackgroundTraditional methods of evaluating mental ...
Neural dynamics of mental state attribution to social robot faces.
Social cognitive and affective neuroscience
Apr 2, 2025
The interplay of mind attribution and emotional responses is considered crucial in shaping human trust and acceptance of social robots. Understanding this interplay can help us create the right conditions for successful human-robot social interaction...
Machine Learning and Deep Learning in Detection of Neonatal Seizures: A Systematic Review.
Journal of evaluation in clinical practice
Apr 1, 2025
BACKGROUND: Neonatal seizures are one of the most prevalent clinical manifestations of neurological conditions, requiring urgent intervention and detection. Machine learning (ML) and Deep Learning (DL) is an emerging promising tool for detecting and ...
Enhanced EEG Forecasting: A Probabilistic Deep Learning Approach.
Neural computation
Mar 18, 2025
Forecasting electroencephalography (EEG) signals, that is, estimating future values of the time series based on the past ones, is essential in many real-time EEG-based applications, such as brain-computer interfaces and closed-loop brain stimulation....
Autism Spectrum Disorder Detection Using Prominent Connectivity Features from Electroencephalography.
International journal of neural systems
Mar 1, 2025
Autism Spectrum Disorder (ASD) is a disorder of brain growth with great variability whose clinical presentation initially shows up during early stages or youth, and ASD follows a repetitive pattern of behavior in most cases. Accurate diagnosis of ASD...
Mortality risk assessment using deep learning-based frequency analysis of electroencephalography and electrooculography in sleep.
Sleep
Feb 10, 2025
STUDY OBJECTIVES: To assess whether the frequency content of electroencephalography (EEG) and electrooculography (EOG) during nocturnal polysomnography (PSG) can predict all-cause mortality.
MDD-SSTNet: detecting major depressive disorder by exploring spectral-spatial-temporal information on resting-state electroencephalography data based on deep neural network.
Cerebral cortex (New York, N.Y. : 1991)
Feb 5, 2025
Major depressive disorder (MDD) is a psychiatric disorder characterized by persistent lethargy that can lead to suicide in severe cases. Hence, timely and accurate diagnosis and treatment are crucial. Previous neuroscience studies have demonstrated t...
[Application Status of Machine Learning in Assisted Diagnosis Techniques of Cardiovascular Diseases].
Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
Jan 30, 2025
In recent years, cardiovascular disease has become a common disease. With the development of machine learning and big data technologies, the processing ability of electrocardiogram (ECG) signals has been greatly enhanced through new computer technolo...
Research on emotion recognition using sparse EEG channels and cross-subject modeling based on CNN-KAN-[Formula: see text] model.
PloS one
Jan 1, 2025
Emotion recognition plays a significant role in artificial intelligence and human-computer interaction. Electroencephalography (EEG) signals, due to their ability to directly reflect brain activity, have become an essential tool in emotion recognitio...
Intelligent Control to Suppress Epileptic Seizures in the Amygdala: In Silico Investigation Using a Network of Izhikevich Neurons.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jan 1, 2025
Closed-loop electricalstimulation of brain structures is one of the most promising techniques to suppress epileptic seizures in drug-resistant refractory patients who are also ineligible to ablative neurosurgery. In this work, an intelligent controll...
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