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Stroke

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Utilizing deep learning via the 3D U-net neural network for the delineation of brain stroke lesions in MRI image.

Scientific reports
The segmentation of acute stroke lesions plays a vital role in healthcare by assisting doctors in making prompt and well-informed treatment choices. Although Magnetic Resonance Imaging (MRI) is a time-intensive procedure, it produces high-fidelity im...

Localization of early infarction on non-contrast CT images in acute ischemic stroke with deep learning approach.

Scientific reports
Localization of early infarction on first-line Non-contrast computed tomogram (NCCT) guides prompt treatment to improve stroke outcome. Our previous study has shown a good performance in the identification of ischemic injury on NCCT. In the present s...

Effects of high-intensity gait training with and without soft robotic exosuits in people post-stroke: a development-of-concept pilot crossover trial.

Journal of neuroengineering and rehabilitation
INTRODUCTION: High-intensity gait training is widely recognized as an effective rehabilitation approach after stroke. Soft robotic exosuits that enhance post-stroke gait mechanics have the potential to improve the rehabilitative outcomes achieved by ...

User Experience Evaluation of Upper Limb Rehabilitation Robots: Implications for Design Optimization: A Pilot Study.

Sensors (Basel, Switzerland)
With the development of science and technology, people are trying to use robots to assist in stroke rehabilitation training. This study aims to analyze the result of the formative test to provide the orientation of upper limb rehabilitation robot des...

In-hospital fall prediction using machine learning algorithms and the Morse fall scale in patients with acute stroke: a nested case-control study.

BMC medical informatics and decision making
BACKGROUND: Falls are one of the most common accidents in medical institutions, which can threaten the safety of inpatients and negatively affect their prognosis. Herein, we developed a machine learning (ML) model for fall prediction in patients with...

Predicting mortality in brain stroke patients using neural networks: outcomes analysis in a longitudinal study.

Scientific reports
In this study, Neural Networks (NN) modelling has emerged as a promising tool for predicting outcomes in patients with Brain Stroke (BS) by identifying key risk factors. In this longitudinal study, we enrolled 332 patients form Imam hospital in Ardab...

A Flexible Wearable Supernumerary Robotic Limb for Chronic Stroke Patients.

Journal of visualized experiments : JoVE
In this study, we present a flexible wearable supernumerary robotic limb that helps chronic stroke patients with finger rehabilitation and grasping movements. The design of this innovative limb draws inspiration from bending pneumatic muscles and the...

Effectiveness of Robotics in Stroke Rehabilitation to Accelerate Upper Extremity Function: Systematic Review.

Occupational therapy international
OBJECTIVE: To examine the effectiveness of robot-assisted therapy (RAT) combined with conventional therapy (CT) compared to CT alone in accelerating upper extremity (UE) recovery poststroke. . We searched five databases: Ovid, MEDLINE, CINAHL, PubMed...

Feasibility, safety, and efficacy of task-oriented mirrored robotic training on upper-limb functions and activities of daily living in subacute poststroke patients: a pilot study.

European journal of physical and rehabilitation medicine
BACKGROUND: Robotic training with high repetitions facilitates upper-limb movements but provides fewer benefits for activities of daily living. Integrating activities of daily living training tasks and mirror therapy into a robot may enhance the func...