Latest AI and machine learning research in seizures for healthcare professionals.
Epilepsy is a globally distributed chronic neurological disorder that may pose a threat to life with...
Wearable devices with continuous monitoring capabilities are critical for the daily detection of epi...
Personalized brain implants have the potential to revolutionize the treatment of neurological disord...
Sleep staging is a crucial task in clinical and research contexts for diagnosing and understanding s...
Quantifying emesis in Suncus murinus (S. murinus) has traditionally relied on direct observation or ...
The risk of adverse effects in Electroconvulsive Therapy (ECT), such as cognitive impairment, can be...
In brain-computer interface (BCI) systems, symmetric positive definite (SPD) manifold within Riemann...
In motor imagery (MI) tasks for brain computer interfaces (BCIs), the spatial covariance matrix (SCM...
High-frequency oscillations (HFOs) in intracranial EEG (iEEG) recordings are critical biomarkers for...
Research suggests that dreams play a role in the regulation of emotional processing and memory conso...
BACKGROUND AND OBJECTIVE: Deep learning models have gained widespread adoption in healthcare for acc...
Understanding cognitive workload improves learning performance and provides insights into human cogn...
Key challenges in upper limb prosthetics include a lack of effective control systems, the often inva...
. Among all BCI paradigms, motion imagery (MI) has gained favor among researchers because it allows ...
Transfer learning is one of the popular methods to solve the problem of insufficient data in subject...
The identification of spikes, as a typical characteristic wave of epilepsy, is crucial for diagnosin...
Identifying new anti-seizure medications (ASMs) is difficult due to limitations in animal-based assa...
Denoising artifacts, such as noise from muscle or cardiac activity, is a crucial and ubiquitous conc...
BACKGROUND: The proportion of traffic accidents caused by fatigue driving is increasing year by year...
Previous deep learning-based brain network research has made significant progress in understanding t...
BACKGROUND: Electroencephalogram (EEG) microstates, which reflect large-scale resting-state networks...