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Stroke

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Bimanual motor skill learning with robotics in chronic stroke: comparison between minimally impaired and moderately impaired patients, and healthy individuals.

Journal of neuroengineering and rehabilitation
BACKGROUND: Most activities of daily life (ADL) require cooperative bimanual movements. A unilateral stroke may severely impair bimanual ADL. How patients with stroke (re)learn to coordinate their upper limbs (ULs) is largely unknown. The objectives ...

Corticomuscular integrated representation of voluntary motor effort in robotic control for wrist-hand rehabilitation after stroke.

Journal of neural engineering
The central-to-peripheral voluntary motor effort (VME) in the affected limb is a dominant force for driving the functional neuroplasticity on motor restoration post-stroke. However, current rehabilitation robots isolated the central and peripheral in...

Deep Learning-Based Diffusion-Weighted Magnetic Resonance Imaging in the Diagnosis of Ischemic Penumbra in Early Cerebral Infarction.

Contrast media & molecular imaging
The prefiltered image was imported into the local higher-order singular value decomposition (HOSVD) denoising algorithm (GL-HOSVD)-optimized diffusion-weighted imaging (DWI) image, which was compared with the deviation correction nonlocal mean (NL me...

Improving interobserver agreement and performance of deep learning models for segmenting acute ischemic stroke by combining DWI with optimized ADC thresholds.

European radiology
OBJECTIVES: To examine the role of ADC threshold on agreement across observers and deep learning models (DLMs) plus segmentation performance of DLMs for acute ischemic stroke (AIS).

Robot-Assisted Therapy Combined with Trunk Restraint in Acute Stroke Patients: A Randomized Controlled Study.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND: Reducing the compensatory mechanism by restraining unnecessary trunk movements may help enhance the effectiveness of robot-assisted therapy.

Application of Deep Learning to Ischemic and Hemorrhagic Stroke Computed Tomography and Magnetic Resonance Imaging.

Seminars in ultrasound, CT, and MR
Deep Learning (DL) algorithm holds great potential in the field of stroke imaging. It has been applied not only to the "downstream" side such as lesion detection, treatment decision making, and outcome prediction, but also to the "upstream" side for ...

The diagnostic levels of evidence of instrumented devices for measuring viscoelastic joint properties and spasticity; a systematic review.

Journal of neuroengineering and rehabilitation
BACKGROUND: Many diagnostic robotic devices have been developed to quantify viscoelastic properties and spasticity of patients with upper motor neuron lesions. However, in clinical practice, subjective and nonvalid clinical scales are still commonly ...

Improved Stroke Care in a Primary Stroke Centre Using AI-Decision Support.

Cerebrovascular diseases extra
BACKGROUND: Patient selection for reperfusion therapies requires significant expertise in neuroimaging. Increasingly, machine learning-based analysis is used for faster and standardized patient selection. However, there is little information on how s...

Is robot-assisted gait training intensity a determinant of functional recovery early after stroke? A pragmatic observational study of clinical care.

International journal of rehabilitation research. Internationale Zeitschrift fur Rehabilitationsforschung. Revue internationale de recherches de readaptation
Gait rehabilitation is a critical factor in functional recovery after a stroke. The aim of this pragmatic observational study was to identify the optimal dose and timing of robot-assisted gait training (RAGT) that can lead to a favourable outcome in ...