INTRODUCTION: Sleep disorders significantly disrupt normal sleep patterns and pose serious health risks. Traditional diagnostic methods, such as questionnaires and polysomnography, often require extensive time and are susceptible to errors. This high...
. Common spatial patterns (CSPs) has been established as a powerful feature extraction method in EEG signal processing with machine learning, but it has shortcomings including sensitivity to noise and rigidity in the value of the weights. Our goal wa...
The Spiking Neural Network (SNN) is a third-generation neural network recognized for its energy efficiency and ability to process spatiotemporal information, closely imitating the behavioral mechanisms of biological neurons in the brain. SNN exhibit ...
INTRODUCTION: Epilepsy is a prevalent chronic neurological disorder, with approximately one-third of patients experiencing intractable epilepsy, often necessitating surgical intervention. Deep brain stimulation (DBS) of the thalamus has been introduc...
To develop and validate a machine learning framework for the classification of distinct seizure onset patterns using intracranial EEG (iEEG) recordings in a non-human primate (NHP) model of penicillin-induced seizures.iEEG data were collected from si...
BACKGROUND: Imagined speech has emerged as a promising paradigm for intuitive control of brain-computer interface (BCI)-based communication systems, providing a means of communication for individuals with severe brain disabilities. In this work, a no...
Emotion recognition is a key research area in artificial intelligence, playing a critical role in enhancing human-computer interaction and optimizing user experience design. This study explores the application and effectiveness of ensemble learning m...
Motor imagery (MI) is a cognitive process requiring mental simulation of physical actions, engaging neural networks that overlap with those activated during actual execution. This study investigated the neural correlates of slow and fast MI in ten he...
Computer methods and programs in biomedicine
Jun 4, 2025
BACKGROUND AND OBJECTIVE: Attention, cognitive workload/fatigue, and emotional states significantly influence learning outcomes, cognitive performance, and human-machine interactions. However, existing assessment methodologies fail to fully capture t...
In recent years, several machine-learning (ML) solutions have been proposed to solve the problems of seizure detection, seizure phase classification, seizure prediction, and seizure onset zone (SOZ) localization, achieving excellent performance with ...
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