A5101972341- EEG and Brain-Computer Interfaces
- Transcranial Magnetic Stimulation Studies
- Stroke Rehabilitation and Recovery
- Gaze Tracking and Assistive Technology
- Muscle activation and electromyography studies
- Neuroscience and Neural Engineering
- Anesthesia and Sedative Agents
- Cancer survivorship and care
- Facial Trauma and Fracture Management
- Heart Rate Variability and Autonomic Control
- Brain Tumor Detection and Classification
- Neuroscience and Neuropharmacology Research
- Functional Brain Connectivity Studies
- Dementia and Cognitive Impairment Research
- Anesthesia and Neurotoxicity Research
- Neurological disorders and treatments
- Congenital Heart Disease Studies
- Endoplasmic Reticulum Stress and Disease
- Hip disorders and treatments
- Spaceflight effects on biology
- Nutrition and Health in Aging
- Sleep and Work-Related Fatigue
- Nerve injury and regeneration
- Alzheimer's disease research and treatments
- Artificial Intelligence in Healthcare and Education
National University Hospital
2015-2025
Central South University
2024
Third Xiangya Hospital
2024
The University of Texas at Arlington
2014
Institute of Basic Medical Sciences of the Chinese Academy of Medical Sciences
2013
Institute of Physiology and Basic Medicine
2013
This single-arm multisite trial investigates the efficacy of neurostyle brain exercise therapy towards enhanced recovery (nBETTER) system, an electroencephalogram (EEG)-based motor imagery brain-computer interface (MI-BCI) employing visual feedback for upper-limb stroke rehabilitation, and presence EEG correlates mental fatigue during BCI usage.A total 13 recruited patients underwent thrice-weekly nBETTER coupled with standard arm over six weeks. Upper-extremity Fugl-Meyer assessment (FMA)...
Introduction: Transcranial direct current stimulation (tDCS) has been shown to modulate cortical plasticity, enhance motor learning and post-stroke upper extremity recovery. It also demonstrated facilitate activation of brain-computer interface (BCI) in stroke patients. We had previously that BCI-assisted imagery (MI-BCI) can improve impairment chronic participants. This study was carried out investigate the effects priming with tDCS prior MI-BCI training patients moderate severe paresis...
Although brain-computer interface (BCI) shows promising prospects to help post-stroke patients recover their motor function, its decoding accuracy is still highly dependent on feature extraction methods. Most current extractors in BCI are classification-based methods, yet very few works from literature use metric learning based methods learn representations for BCI. In this paper, we propose a deep method, Weighted Convolutional Siamese Network (WCSN) electroencephalogram (EEG) signal. This...
Chat Generative Pre-trained Transformer (ChatGPT) is a new machine learning tool that allows patients to access health information online, specifically compared Google, the most commonly used search engine in United States. Patients can use ChatGPT better understand medical issues. This study two engines based on: (i) frequently asked questions (FAQs) about Femoroacetabular Impingement Syndrome (FAI), (ii) corresponding answers these FAQs, and (iii) FAQs yielding numerical response.
Upper limb weakness following stroke poses a significant global psychosocial and economic burden. Non-invasive brain stimulation (NIBS) is potential adjunctive treatment in rehabilitation. However, traditional approaches to rebalance interhemispheric inhibition may not be effective for all patients. The supportive role of the contralesional hemisphere recovery upper motor function has been supported by animal clinical studies, particularly those with severe strokes. This review aims provide...
The convolutional neural network (CNN) automatically learns EEG representations in higher and nonlinear space via backpropagation outputs the predictions an end-to-end manner. Owing to these advantages, CNN has been used decode electroencephalogram (EEG) drive brain computer interface (BCI). However, its applications BCI-assisted post-stroke neurorehabilitation remain limited for it is unable address inherent session-to-session non-stationarity between initial calibration session subsequent...
Abstract Alzheimer’s disease (AD) is a relatively common senile neurodegenerative and the main manifestation of dementia. In pathological changes AD, asymmetry brain also changes. Therefore, finding an early diagnosis method AD based on key to treatment Alzheimer’s. Magnetic resonance (MR) imaging can quantitatively reflect structural functional various tissues in brain. It has advantages non-invasive, high spatial resolution, non-radiation, been widely used AD. this work, asymmetric images...