Neural networks : the official journal of the International Neural Network Society
Jun 24, 2025
Spiking neural networks (SNNs) aim to simulate the human brain neural network, using sparse spike event streams for effective and energy-efficient spatio-temporal signal processing. This paper proposes a lightweight SNN model for electroencephalogram...
In a brain-computer interface (BCI), a primary objective is to reduce calibration time by recording as few as possible novel data points to (re-)train decoder models.Minimizing the calibration can be crucial for enhancing the usability of a BCI appli...
EEG signal classification for neurological disorders is a very critical task in the healthcare field, demanding accuracy and efficiency. Due to the diversity of these disorders and the complexity of the EEG signals, the task of diagnosing these disor...
Computer methods and programs in biomedicine
Jun 22, 2025
BACKGROUND AND OBJECTIVE: Decoding visual information from electroencephalography (EEG) signals is crucial in neuroscience and artificial intelligence. While existing methods have been able to extract high-level features such as object categories, th...
Epileptic seizures can occur unpredictably, making real-time monitoring and early warning systems critical, especially in neonatal patients, where timely intervention can significantly improve outcomes. Neonatal seizures are often subtle and difficul...
The widespread use of 3D stereoscopic technology has drawn attention to the problem of visual discomfort, several studies have used EEG to assess visual comfort and discomfort phenomena, but there is a lack of scientific basis for the selection of el...
Journal of neuroengineering and rehabilitation
Jun 18, 2025
BACKGROUND: Robot-assisted gait training is more effective in improving lower limb function and walking ability in stroke patients compared to conventional rehabilitation, but the neural mechanisms remain unclear. This study aims to explore the effec...
Biomedical physics & engineering express
Jun 18, 2025
Low-beta (L, 13-20 Hz) power plays a key role in upper-limb motor control and afferent processing, making it a strong candidate for a neurophysiological biomarker. We investigate the test-retest reliability of Lpower and kinematic features from a rob...
Electroencephalographic (EEG) microstates, as a non-invasive and high-temporal-resolution tool for analyzing time-space features of brain activity, have been validated and applied in various research domains. However, current methods for EEG microsta...
BACKGROUND: Numerous studies have revealed abnormalities in EEG microstate in insomnia, primarily quantified using linear features, whereas nonlinear metrics remain underexplored. This study aimed to compare linear and nonlinear features and further ...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.