AIMC Topic: Stroke

Clear Filters Showing 1081 to 1090 of 1213 articles

High Compliance Pneumatic Actuators to Promote Finger Extension in Stroke Survivors.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Compliant pneumatic systems are well suited for wearable robotic applications. The actuators are lightweight, conformable to irregular shapes, and tolerant of uncontrolled degrees of freedom. These attributes are especially desirable for hand exoskel...

Gaze-controlled Robot-assisted Painting in Virtual Reality for Upper-limb Rehabilitation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Stroke is the leading cause of adult disability. Robot-assisted rehabilitation systems show great promise for motor recovery after a stroke. In this work, we present a gazecontrolled robotic system for upper limb rehabilitation. Subjects perform a pa...

Towards Stroke Biomarkers on Fundus Retinal Imaging: A Comparison Between Vasculature Embeddings and General Purpose Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Fundus Retinal imaging is an easy-to-acquire modality typically used for monitoring eye health. Current evidence indicates that the retina, and its vasculature in particular, is associated with other disease processes making it an ideal candidate for...

The structural connectome and motor recovery after stroke: predicting natural recovery.

Brain : a journal of neurology
Stroke patients vary considerably in terms of outcomes: some patients present 'natural' recovery proportional to their initial impairment (fitters), while others do not (non-fitters). Thus, a key challenge in stroke rehabilitation is to identify indi...

A Bayesian optimization approach for rapidly mapping residual network function in stroke.

Brain : a journal of neurology
Post-stroke cognitive and linguistic impairments are debilitating conditions, with limited therapeutic options. Domain-general brain networks play an important role in stroke recovery and characterizing their residual function with functional MRI has...

Stroke risk prediction using machine learning: a prospective cohort study of 0.5 million Chinese adults.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To compare Cox models, machine learning (ML), and ensemble models combining both approaches, for prediction of stroke risk in a prospective study of Chinese adults.

A data-driven approach to post-stroke aphasia classification and lesion-based prediction.

Brain : a journal of neurology
Aphasia is an acquired impairment in the production or comprehension of language, typically caused by left hemisphere stroke. The subtyping framework used in clinical aphasiology today is based on the Wernicke-Lichtheim model of aphasia formulated in...

Predictors of bleeding event among elderly patients with mechanical valve replacement using random forest model: A retrospective study.

Medicine
Available classification tools and risk factors predicting bleeding events in elderly patients after mechanical valve replacement may not be suitable in Asian populations. Thus, we aimed to identify an accurate model for predicting bleeding in elderl...

A 10-item Fugl-Meyer Motor Scale Based on Machine Learning.

Physical therapy
OBJECTIVE: The Fugl-Meyer motor scale (FM) is a well-validated measure for assessing upper extremity and lower extremity motor functions in people with stroke. The FM contains numerous items (50), which reduces its clinical usability. The purpose of ...