AI Medical Compendium Topic:
Stroke

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Overground walking training with the i-Walker, a robotic servo-assistive device, enhances balance in patients with subacute stroke: a randomized controlled trial.

Journal of neuroengineering and rehabilitation
BACKGROUND: Patients affected by mild stroke benefit more from physiological overground walking training than walking-like training performed in place using specific devices. The aim of the study was to evaluate the effects of overground robotic walk...

Extracting a stroke phenotype risk factor from Veteran Health Administration clinical reports: an information content analysis.

Journal of biomedical semantics
BACKGROUND: In the United States, 795,000 people suffer strokes each year; 10-15 % of these strokes can be attributed to stenosis caused by plaque in the carotid artery, a major stroke phenotype risk factor. Studies comparing treatments for the manag...

Compensating Hand Function in Chronic Stroke Patients Through the Robotic Sixth Finger.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
A novel solution to compensate hand grasping abilities is proposed for chronic stroke patients. The goal is to provide the patients with a wearable robotic extra-finger that can be worn on the paretic forearm by means of an elastic band. The proposed...

The Effects of Combination of Robot-Assisted Therapy With Task-Specific or Impairment-Oriented Training on Motor Function and Quality of Life in Chronic Stroke.

PM & R : the journal of injury, function, and rehabilitation
BACKGROUND: Robot-assisted therapy (RT) is a promising intervention for stroke rehabilitation. RT hybridized with therapist-mediated therapy (eg, RT plus task-specific or impairment-oriented training) may possibly yield functionally relevant improvem...

A Machine Learning Framework for Gait Classification Using Inertial Sensors: Application to Elderly, Post-Stroke and Huntington's Disease Patients.

Sensors (Basel, Switzerland)
Machine learning methods have been widely used for gait assessment through the estimation of spatio-temporal parameters. As a further step, the objective of this work is to propose and validate a general probabilistic modeling approach for the classi...

Predicting Functional Recovery in Chronic Stroke Rehabilitation Using Event-Related Desynchronization-Synchronization during Robot-Assisted Movement.

BioMed research international
Although rehabilitation robotics seems to be a promising therapy in the rehabilitation of the upper limb in stroke patients, consensus is still lacking on its additive effects. Therefore, there is a need for determining the possible success of roboti...

Robotic Quantification of Position Sense in Children With Perinatal Stroke.

Neurorehabilitation and neural repair
Background Perinatal stroke is the leading cause of hemiparetic cerebral palsy. Motor deficits and their treatment are commonly emphasized in the literature. Sensory dysfunction may be an important contributor to disability, but it is difficult to me...

Prediction of final infarct volume on subacute MRI by quantifying cerebral edema in ischemic stroke.

Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism
Final infarct volume in stroke trials is assessed on images obtained between 30 and 90 days after stroke onset. Imaging at such delayed timepoints is problematic because patients may be lost to follow-up or die before the scan. Obtaining an early ass...