AIMC Topic: Stroke

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Image-level detection of arterial occlusions in 4D-CTA of acute stroke patients using deep learning.

Medical image analysis
The triage of acute stroke patients is increasingly dependent on four-dimensional CTA (4D-CTA) imaging. In this work, we present a convolutional neural network (CNN) for image-level detection of intracranial anterior circulation artery occlusions in ...

User-Driven Functional Movement Training With a Wearable Hand Robot After Stroke.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
We studied the performance of a robotic orthosis designed to assist the paretic hand after stroke. It is wearable and fully user-controlled, serving two possible roles: as a therapeutic tool that facilitates device-mediated hand exercises to recover ...

Neuroimaging and deep learning for brain stroke detection - A review of recent advancements and future prospects.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In recent years, deep learning algorithms have created a massive impact on addressing research challenges in different domains. The medical field also greatly benefits from the use of improving deep learning models which sav...

Early experience utilizing artificial intelligence shows significant reduction in transfer times and length of stay in a hub and spoke model.

Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences
BACKGROUND: Recently approved artificial intelligence (AI) software utilizes AI powered large vessel occlusion (LVO) detection technology which automatically identifies suspected LVO through CT angiogram (CTA) imaging and alerts on-call stroke teams....

Deep Learning Based Software to Identify Large Vessel Occlusion on Noncontrast Computed Tomography.

Stroke
BACKGROUND AND PURPOSE: Reliable recognition of large vessel occlusion (LVO) on noncontrast computed tomography (NCCT) may accelerate identification of endovascular treatment candidates. We aim to validate a machine learning algorithm (MethinksLVO) t...

Artificial intelligence for decision support in acute stroke - current roles and potential.

Nature reviews. Neurology
The identification and treatment of patients with stroke is becoming increasingly complex as more treatment options become available and new relationships between disease features and treatment response are continually discovered. Consequently, clini...

Neurocognitive robot-assisted rehabilitation of hand function: a randomized control trial on motor recovery in subacute stroke.

Journal of neuroengineering and rehabilitation
BACKGROUND: Hand function is often impaired after stroke, strongly affecting the ability to perform daily activities. Upper limb robotic devices have been developed to complement rehabilitation therapy offered to persons who suffered a stroke, but th...

Repetitions, duration and intensity of upper limb practice following the implementation of robot assisted therapy with sub-acute stroke survivors: an observational study.

Disability and rehabilitation. Assistive technology
BACKGROUND: Robot assisted upper limb (UL) therapy has been identified as an intervention with the potential to help improve the amount of practice performed by stroke survivors.

Changes in electroencephalography complexity and functional magnetic resonance imaging connectivity following robotic hand training in chronic stroke.

Topics in stroke rehabilitation
In recent years, robotic training has been utilized for recovery of motor control in patients with motor deficits. Along with clinical assessment, electrical patterns in the brain have emerged as a marker for studying changes in the brain associated...

Denoising Algorithm for Event-Related Desynchronization-Based Motor Intention Recognition in Robot-assisted Stroke Rehabilitation Training with Brain-Machine Interaction.

Journal of neuroscience methods
BACKGROUND: Rehabilitation robots integrated with brain-machine interaction (BMI) can facilitate stroke patients' recovery by closing the loop between motor intention and actual movement. The main challenge is to identify the patient's motor intentio...