IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
39269794
Bilateral robotic rehabilitation has proven helpful in the recovery of upper limb motor function in patients with stroke, but its effects on the cortical reorganization mechanisms underlying recovery are still unclear. This pilot Randomized Controlle...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
39236133
The EEG is a widely utilized neural signal source, particularly in motor imagery-based brain-computer interface (MI-BCI), offering distinct advantages in applications like stroke rehabilitation. Current research predominantly concentrates on the bila...
BACKGROUND: The aim of the study was to assess the inter-rater and intra-rater agreement of measurements performed with the Luna EMG (electromyography) multifunctional robot, a tool for evaluation of upper limb proprioception in individuals with stro...
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
39218611
Lower limb exoskeleton rehabilitation robots are used to improve or restore the walking and movement ability of people with lower limb movement disorders. However, the required functions for patients differ based on various diseases. For example, pat...
Archives of physical medicine and rehabilitation
39218244
OBJECTIVE: To derive and validate a prediction model for minimal clinically important differences (MCIDs) in upper extremity (UE) motor function after intention-driven robotic hand training using residual voluntary electromyography (EMG) signals from...
PURPOSE: Robotic devices for upper-limb neurorehabilitation allow an increase in intensity of practice, often relying on video game-based training strategies with limited capacity to individualise training and integrate functional training. This stud...
This study investigated whether machine learning (ML) has better predictive accuracy than logistic regression analysis (LR) for gait independence at discharge in subacute stroke patients (n = 843) who could not walk independently at admission. We dev...
BACKGROUND: Accurately predicting the walking independence of stroke patients is important. Our objective was to determine and compare the performance of logistic regression (LR) and three machine learning models (eXtreme Gradient Boosting (XGBoost),...
Journal of neuroengineering and rehabilitation
39232831
BACKGROUND: To overcome the application limitations of functional electrical stimulation (FES), such as fatigue or nonlinear muscle response, the combination of neuroprosthetic systems with robotic devices has been evaluated, resulting in hybrid syst...