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Stroke

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The Impact of Cognitive Impairment on Robot-Based Upper-Limb Motor Assessment in Chronic Stroke.

Neurorehabilitation and neural repair
BACKGROUND: Chronic upper extremity motor deficits are present in up to 65% of stroke survivors, and cognitive impairment is prevalent in 46-61% of stroke survivors even 10 years after their stroke. Robot-assisted therapy programs tend to focus on mo...

Deep Learning-Based Subtask Segmentation of Timed Up-and-Go Test Using RGB-D Cameras.

Sensors (Basel, Switzerland)
The timed up-and-go (TUG) test is an efficient way to evaluate an individual's basic functional mobility, such as standing up, walking, turning around, and sitting back. The total completion time of the TUG test is a metric indicating an individual's...

Effectiveness of robot-assisted virtual reality mirror therapy for upper limb motor dysfunction after stroke: study protocol for a single-center randomized controlled clinical trial.

BMC neurology
BACKGROUND: Upper limb motor dysfunction is a common sequela of stroke, and its clinical efficacy needs to be improved. This protocol describes a trial to verify the clinical efficacy of robot-assisted virtual reality mirror therapy (RAVRMT) in impro...

Design of Wearable Hand Rehabilitation Glove With Bionic Fiber-Reinforced Actuator.

IEEE journal of translational engineering in health and medicine
BACKGROUND: The hand motor function is lost and activities in daily life (ADLs) are affected due to some illnesses such as stroke and hemiplegia. As a coping way, we present a wearable rehabilitation glove with the bionic actuator for restoring the h...

Antistroke Network Pharmacological Prediction of Xiaoshuan Tongluo Recipe Based on Drug-Target Interaction Based on Deep Learning.

Computational and mathematical methods in medicine
Stroke is a common cerebrovascular disease that threatens human health, and the search for therapeutic drugs is the key to treatment. New drug discovery was driven by many accidental factors in the early stage. With the deepening of research, disease...

Use of Machine Learning to Develop Prediction Models for Mortality and Stroke in Patients Undergoing Balloon Aortic Valvuloplasty.

Cardiovascular revascularization medicine : including molecular interventions
OBJECTIVE: To develop an artificial intelligence, machine learning prediction model for estimating in-hospital mortality and stroke in patients undergoing balloon aortic valvuloplasty (BAV).

Unsupervised Deep Learning for Stroke Lesion Segmentation on Follow-up CT Based on Generative Adversarial Networks.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Supervised deep learning is the state-of-the-art method for stroke lesion segmentation on NCCT. Supervised methods require manual lesion annotations for model development, while unsupervised deep learning methods such as gener...

Effect of Robot-Assisted Training on Unilateral Spatial Neglect After Stroke: Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Neurorehabilitation and neural repair
BACKGROUND: Several studies have shown that robotic devices can effectively improve motor function in stroke patients through limb activation. However, the effects of robot-assisted therapy on perceptual deficits after stroke is unclear.

Short and long-term effects of robot-assisted therapy on upper limb motor function and activity of daily living in patients post-stroke: a meta-analysis of randomized controlled trials.

Journal of neuroengineering and rehabilitation
OBJECTIVE: To investigate the effect of robot-assisted therapy (RAT) on upper limb motor control and activity function in poststroke patients compared with that of non-robotic therapy.

Effects of robotic rehabilitation on recovery of hand functions in acute stroke: A preliminary randomized controlled study.

Acta neurologica Scandinavica
OBJECTIVE: The aim of this study was to investigate the effects of EMG-driven robotic rehabilitation on hand motor functions and daily living activities of patients with acute ischemic stroke.