AIMC Topic: Electroencephalography
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Brain-Computer Interface-controlled Upper Limb Robotic System for Enhancing Daily Activities in Stroke Patients.
Journal of visualized experiments : JoVE
Apr 18, 2025
This study introduces a Brain-Computer Interface (BCI)-controlled upper limb assistive robot for post-stroke rehabilitation. The system utilizes electroencephalogram (EEG) and electrooculogram (EOG) signals to help users assist upper limb function in...
Deep learning-based EEG source imaging is robust under varying electrode configurations.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Apr 16, 2025
OBJECTIVES: Previous research has underscored the necessity of high-density EEG for accurate and reliable EEG source imaging (ESI) results with conventional ESI methods, limiting their utility in clinical settings with only low-density EEG available....
Predicting Intraoperative Burst Suppression Using Preoperative EEG and Patient Characteristics.
International journal of neural systems
Apr 16, 2025
Burst suppression (BS) is an electroencephalogram (EEG) pattern observed in patients undergoing general anesthesia. The occurrence of BS is associated with adverse outcomes such as postoperative delirium, extended recovery time, and increased postope...
Multi-scale convolutional transformer network for motor imagery brain-computer interface.
Scientific reports
Apr 15, 2025
Brain-computer interface (BCI) systems allow users to communicate with external devices by translating neural signals into real-time commands. Convolutional neural networks (CNNs) have been effectively utilized for decoding motor imagery electroencep...
AADNet: Exploring EEG Spatiotemporal Information for Fast and Accurate Orientation and Timbre Detection of Auditory Attention Based on a Cue-Masked Paradigm.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Apr 14, 2025
Auditory attention decoding from electroencephalogram (EEG) could infer to which source the user is attending in noisy environments. Decoding algorithms and experimental paradigm designs are crucial for the development of technology in practical appl...
Review of sEMG for Exoskeleton Robots: Motion Intention Recognition Techniques and Applications.
Sensors (Basel, Switzerland)
Apr 13, 2025
The global aging trend is becoming increasingly severe, and the demand for life assistance and medical rehabilitation for frail and disabled elderly people is growing. As the best solution for assisting limb movement, guiding limb rehabilitation, and...
A diagnosis and prediction algorithm for juvenile myoclonic epilepsy based on clinical and quantitative EEG features.
Seizure
Apr 12, 2025
OBJECTIVE: To develop an objective ensemble machine learning model combining clinical features and quantitative EEG metrics (phase locking value [PLV] and multiscale sample entropy [MSE]) to support accurate diagnosis of juvenile myoclonic epilepsy (...
Machine learning-based differentiation of schizophrenia and bipolar disorder using multiscale fuzzy entropy and relative power from resting-state EEG.
Translational psychiatry
Apr 12, 2025
Schizophrenia (SZ) and bipolar disorder (BD) pose diagnostic challenges due to overlapping clinical symptoms and genetic factors, often resulting in misdiagnosis and suboptimal treatment outcomes. This study aimed to identify EEG-based biomarkers tha...
Artificial intelligence for the detection of interictal epileptiform discharges in EEG signals.
Revue neurologique
Apr 10, 2025
INTRODUCTION: Over the past decades, the integration of modern technologies - such as electronic health records, cloud computing, and artificial intelligence (AI) - has revolutionized the collection, storage, and analysis of medical data in neurology...
Exploring cortical excitability in children with cerebral palsy through lower limb robot training based on MI-BCI.
Scientific reports
Apr 10, 2025
This study aims to compare brain activity differences under the motor imagery-brain-computer interface (MI-BCI), motor imagery (MI), and resting (REST) paradigms through EEG microstate and functional connectivity (FC) analysis, providing a theoretica...
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