IEEE transactions on neural networks and learning systems
Jun 1, 2025
Granger causality (GC) effective connectivity (EC) calculated from electroencephalogram (EEG) signals has been widely used in mental disorder detection. However, the existing methods only take into account linear dynamics or nonlinear dynamics within...
IEEE transactions on biomedical circuits and systems
Jun 1, 2025
Driven by the progress in efficient embedded processing, there is an accelerating trend toward running machine learning models directly on wearable Brain-Machine Interfaces (BMIs) to improve portability and privacy and maximize battery life. However,...
IEEE journal of biomedical and health informatics
Jun 1, 2025
Electroencephalography (EEG) signals are often contaminated with various physiological artifacts, seriously affecting the quality of subsequent analysis. Therefore, removing artifacts is an essential step in practice. As of now, deep learning-based E...
Recent studies have demonstrated that the representations of artificial neural networks (ANNs) can exhibit notable similarities to cortical representations when subjected to identical auditory sensory inputs. In these studies, the ability to predict ...
Data augmentation has been demonstrated to improve the classification accuracy of deep learning models in steady-state visual evoked potential-based brain-computer interfaces (BCIs), particularly when dealing with limited electroencephalography (EEG)...
Generative artificial intelligence's (GenAI) fast progress has opened up new possibilities, but it has also increased the likelihood of service failure. This study investigates how belief priming affects users' intention to switch following a failure...
Functional connectivity (FC) analyses of intracranial EEG (iEEG) signals can potentially improve the mapping of epileptic networks in drug-resistant focal epilepsy. However, it remains unclear whether FC-based metrics provide additional value beyond ...
Biomedical physics & engineering express
May 22, 2025
Electroencephalography (EEG) is essential for studying infant brain activity but is highly susceptible to artifacts due to infants' movements and physiological variability. Manual artifact detection is labor-intensive and subjective, underscoring the...
Identifying likely placebo responders can help design more efficient clinical trials by stratifying participants, reducing sample size requirements, and enhancing the detection of true drug effects. In response to this need, we developed a deep convo...
Dementia spectrum disorders, characterized by progressive cognitive decline, pose a significant global health burden. Early screening and diagnosis are essential for timely and accurate treatment, improving patient outcomes and quality of life. This ...
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