. Meditation and mindfulness are increasingly recognized as important in improving mental well-being. However, electroencephalography (EEG)-based neurofeedback systems supporting these practices typically fail to generalize to unseen subjects. This s...
Biomedical physics & engineering express
Dec 18, 2025
. To enhance the decoding accuracy and information transfer rate of steady-state visual evoked potential-based brain-computer interface (SSVEP-BCI) systems and to reduce inter-subject variability for broader SSVEP-BCI applications, a dual-channel TRC...
The current gold standard for detecting epileptic seizures is in-hospital video-Electroencephalography (vEEG), but vEEG is resource-intensive and imposes considerable burdens on patients and caregivers. Wearable devices offer an alternative to monito...
Biomedical physics & engineering express
Dec 16, 2025
While peripheral mechanisms of proprioception are well understood, the cortical processing of its feedback during dynamic and complex movements remains less clear. Corticokinematic coherence (CKC), which quantifies the coupling between limb movements...
Alzheimer's Disease (AD) is a very common neurodegenerative disorders and early detection using electroencephalography (EEG) can enable timely intervention, however, existing computational models often lack robustness, interpretability, and clinical ...
Automated electroencephalography (EEG)-based epilepsy diagnosis has reported near-perfect accuracies for almost two decades on a benchmark dataset, yet virtually no system is used in routine care. We critically re-examined this translation gap by rep...
Brain-computer interface (BCI) technology enables direct communication between the human brain and external devices by decoding electroencephalography (EEG)signals into actionable commands. As a noninvasive and portable modality, EEG-based BCIs hold ...
Biomedical physics & engineering express
Dec 10, 2025
Major Depressive Disorder (MDD) diagnosis through Electroencephalography (EEG) is hindered by the non-stationary characteristics of neural oscillations and the limited adaptability of conventional classification frameworks. Static ensemble models, wh...
OBJECTIVE: Neuropsychiatric disorders are characterized by high complexity and comorbidity, imposing a substantial burden on both patients and society. However, their elusive pathogenic mechanisms impede accurate clinical diagnosis and effective inte...
Epilepsy affects around 50 million people globally, causing significant burdens. While many methods predict seizures, current models struggle with handling spatiotemporal features and balancing accuracy with computational efficiency.This paper introd...
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