AIMC Topic: Stroke

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A comparison of the effects and usability of two exoskeletal robots with and without robotic actuation for upper extremity rehabilitation among patients with stroke: a single-blinded randomised controlled pilot study.

Journal of neuroengineering and rehabilitation Oct 19, 2020
BACKGROUND: Robotic rehabilitation of stroke survivors with upper extremity dysfunction may yield different outcomes depending on the robot type. Considering that excessive dependence on assistive force by robotic actuators may interfere with the pat...
Stroke Outcome Assessment, Health Care Exoskeleton Device Upper Extremity Stroke Rehabilitation Male Middle Aged Pilot Projects Robotics Humans Female Aged Adult
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Testing a convolutional neural network-based hippocampal segmentation method in a stroke population.

Human brain mapping Oct 16, 2020
As stroke mortality rates decrease, there has been a surge of effort to study poststroke dementia (PSD) to improve long-term quality of life for stroke survivors. Hippocampal volume may be an important neuroimaging biomarker in poststroke dementia, a...
Stroke Quality Control Hippocampus Datasets as Topic Neuroimaging Humans Neural Networks, Computer Image Processing, Computer-Assisted Magnetic Resonance Imaging
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Effects of walking distance over robot-assisted training on walking ability in chronic stroke patients.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia Oct 16, 2020
An understanding of the dose-response during training is important to identify the rehabilitation programs to obtain the improvement in chronic stroke patients. The purpose of this study was to determine whether distance-dose (distance walked across ...
Gait Exercise Therapy Exoskeleton Device Stroke Rehabilitation Walk Test Treatment Outcome Chronic Disease Robotics Stroke Walking Young Adult Adult Male Middle Aged Humans Female Aged Aged, 80 and over
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A deep-learning system for the assessment of cardiovascular disease risk via the measurement of retinal-vessel calibre.

Nature biomedical engineering Oct 12, 2020
Retinal blood vessels provide information on the risk of cardiovascular disease (CVD). Here, we report the development and validation of deep-learning models for the automated measurement of retinal-vessel calibre in retinal photographs, using divers...
Risk Assessment Aged Humans Glycated Hemoglobin Retinal Vessels Retrospective Studies Aged, 80 and over Deep Learning Cholesterol Image Interpretation, Computer-Assisted Hypertensive Retinopathy Female Body Mass Index Adult Stroke Datasets as Topic Risk Factors Blood Pressure Myocardial Infarction Male Coronary Disease Middle Aged Photography Retina
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Characterization and wearability evaluation of a fully portable wrist exoskeleton for unsupervised training after stroke.

Journal of neuroengineering and rehabilitation Oct 7, 2020
BACKGROUND: Chronic hand and wrist impairment are frequently present following stroke and severely limit independence in everyday life. The wrist orientates and stabilizes the hand before and during grasping, and is therefore of critical importance i...
Humans Activities of Daily Living Female Range of Motion, Articular Aged Male Exoskeleton Device Middle Aged Stroke Rehabilitation Robotics Wrist Joint Equipment Design Stroke
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Technology-assisted stroke rehabilitation.

Neurology Sep 30, 2020
Humans Stroke Technology Stroke Rehabilitation Robotics Telerehabilitation
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Detecting Large Vessel Occlusion at Multiphase CT Angiography by Using a Deep Convolutional Neural Network.

Radiology Sep 29, 2020
Background Large vessel occlusion (LVO) stroke is one of the most time-sensitive diagnoses in medicine and requires emergent endovascular therapy to reduce morbidity and mortality. Leveraging recent advances in deep learning may facilitate rapid dete...
Middle Aged Cerebral Angiography Retrospective Studies Contrast Media Humans Female Stroke Aged Brain Ischemia Neural Networks, Computer Sensitivity and Specificity Computed Tomography Angiography Male
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Kinematic parameters obtained with the ArmeoSpring for upper-limb assessment after stroke: a reliability and learning effect study for guiding parameter use.

Journal of neuroengineering and rehabilitation Sep 29, 2020
BACKGROUND: After stroke, kinematic measures obtained with non-robotic and robotic devices are highly recommended to precisely quantify the sensorimotor impairments of the upper-extremity and select the most relevant therapeutic strategies. Although ...
Stroke Exoskeleton Device Upper Extremity Stroke Rehabilitation Reproducibility of Results Humans Male Aged Learning Middle Aged Adult Female Psychometrics Biomechanical Phenomena Recovery of Function Robotics
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Predicting clinically significant motor function improvement after contemporary task-oriented interventions using machine learning approaches.

Journal of neuroengineering and rehabilitation Sep 29, 2020
BACKGROUND: Accurate prediction of motor recovery after stroke is critical for treatment decisions and planning. Machine learning has been proposed to be a promising technique for outcome prediction because of its high accuracy and ability to process...
Humans Machine Learning Prognosis Female Aged Recovery of Function Stroke Male Physical Therapy Modalities Middle Aged Stroke Rehabilitation Quality of Life ROC Curve
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Development and Validation of Machine Learning-Based Prediction for Dependence in the Activities of Daily Living after Stroke Inpatient Rehabilitation: A Decision-Tree Analysis.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Sep 28, 2020
BACKGROUND AND PURPOSE: Accurate prediction using simple and changeable variables is clinically meaningful because some known-predictors, such as stroke severity and patients age cannot be modified with rehabilitative treatment. There are limited cli...
Risk Assessment Treatment Outcome Inpatients Decision Trees Humans Recovery of Function Mobility Limitation Predictive Value of Tests Risk Factors Clinical Decision Rules Stroke Machine Learning Aged Activities of Daily Living Databases, Factual Aged, 80 and over Stroke Rehabilitation Female Male Reproducibility of Results Middle Aged
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