Schizophrenia is a complex psychiatric disorder that disrupts cognition, emotions, and social behavior. Timely and accurate diagnosis is essential for effective treatment. Traditional diagnostic methods relying on clinical assessments have limitation...
The longitudinal course of epilepsy remains largely unpredictable. This study aimed to predict final outcome and classify dynamic longitudinal trajectories using artificial intelligence. A total of 2586 patients who first visited our epilepsy special...
While deep learning has enabled the decoding of language from intracranial brain recordings, achieving this with non-invasive recordings remains an open challenge. We introduce a deep learning pipeline to decode individual words from electro- (EEG) a...
Schizophrenia (SZ) is increasingly recognized as a network disorder marked by abnormal functional connectivity, yet the clinical utility of fMRI remains limited. Electroencephalography (EEG) provides a more practical alternative, though conventional ...
With the advancement of deep learning technologies, more and more researchers have begun developing end-to-end automatic sleep stage classification frameworks. However, these frameworks typically require access to large electroencephalogram (EEG) dat...
Biomedical physics & engineering express
Nov 25, 2025
As physiological artifacts commonly overlap with EEG signals in both time and frequency domains, developing an effective end-to-end EEG artifact removal method is essential for a brain-computer interface (BCI) system. An end-to-end artifact removal m...
Brain-computer interfaces (BCIs) hold significant promise for restoring communication in individuals with severe motor or speech impairments. Imagined handwriting, as a form of motor imagery, offers an intuitive paradigm for character-level neural de...
Accurate detection of user intention is a critical requirement for intelligent control systems in upper-limb rehabilitation robots. However, electromyography (EMG)-based recognition can degrade significantly under muscle fatigue. To address this limi...
The brain condition known as epilepsy has an impact on patients' quality of life. The need for computer-automated diagnosis systems (CADS) has arisen due to the shortcomings of conventional clinical and machine learning techniques as well as the shor...
Passive brain-computer interface (BCI) based on electroencephalography (EEG) has gained traction as reliable method for monitoring human vigilance in attention-demanding critical contexts. Unfortunately, the lack of extensive public datasets compromi...
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