AI Medical Compendium Topic:
Stroke

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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...

Automatic detection of acute ischemic stroke using non-contrast computed tomography and two-stage deep learning model.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Currently, it is challenging to detect acute ischemic stroke (AIS)-related changes on computed tomography (CT) images. Therefore, we aimed to develop and evaluate an automatic AIS detection system involving a two-stage deep ...

Machine Learning Prediction of Stroke Mechanism in Embolic Strokes of Undetermined Source.

Stroke
BACKGROUND AND PURPOSE: One-fifth of ischemic strokes are embolic strokes of undetermined source (ESUS). Their theoretical causes can be classified as cardioembolic versus noncardioembolic. This distinction has important implications, but the categor...

Multi-frequency symmetry difference electrical impedance tomography with machine learning for human stroke diagnosis.

Physiological measurement
OBJECTIVE: Multi-frequency symmetry difference electrical impedance tomography (MFSD-EIT) can robustly detect and identify unilateral perturbations in symmetric scenes. Here, an investigation is performed to assess if the algorithm can be successfull...

Caregiver burden in stroke inpatients: a randomized study comparing robot-assisted gait training and conventional therapy.

Acta neurologica Belgica
The effects of caregiver burden during the inpatient rehabilitation period have not yet been investigated. The purpose of this study was to evaluate the burden on stroke survivors' caregivers during the inpatient rehabilitation period, and to compare...

Effects of Exoskeletal Lower Limb Robot Training on the Activities of Daily Living in Stroke Patients: Retrospective Pre-Post Comparison Using Propensity Score Matched Analysis.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
PURPOSE: There is limited evidence of gait training using newly developed exoskeletal lower limb robot called Hybrid Assistive Limb (HAL) on the function and ability to perform ADL in stroke patients. In clinical settings, we frequently find it chall...

Tele-robotics and artificial-intelligence in stroke care.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
In the last forty years, the field of medicine has experienced dramatic shifts in technology-enhanced surgical procedures - from its initial use in 1985 for neurosurgical biopsies to current implementation of systems such as magnetic-guided catheters...

Stroke prognostication for discharge planning with machine learning: A derivation study.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Post-stroke discharge planning may be aided by accurate early prognostication. Machine learning may be able to assist with such prognostication. The study's primary aim was to evaluate the performance of machine learning models using admission data t...