Latest AI and machine learning research in neurology for healthcare professionals.
BACKGROUND: Spinal cord injury (SCI) is a severe neurological disorder associated not only with ongoing medical complications but also with a significant loss of mobility and participation. The introduction of robotic technologies to recover lower limb function has been greatly employed in the rehabilitative practice. The aim of this preliminary report were to evaluate the efficacy, the feasibilit...
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 classification of different pathological gaits. Specifically, the presented methodology was tested on gait data recorded on two pathological populations (Hu...
Developmental dyslexia has been hypothesized to result from multiple causes and exhibit multiple manifestations, implying a distributed multidimension...
Gait abnormalities following neurological disorders are often disabling, negatively affecting patients' quality of life. Therefore, regaining of walki...
Rodent models of spinal cord injury are critical for the development of treatments for upper limb motor impairment in humans, but there are few method...
Although rehabilitation robotics seems to be a promising therapy in the rehabilitation of the upper limb in stroke patients, consensus is still lackin...
A generalized predictive closed-loop control strategy to improve the basal ganglia activity patterns in Parkinson's disease (PD) is explored in this p...
We present a novel approach aimed at removing electrocardiogram (ECG) perturbation from single-channel surface electromyogram (EMG) recordings by mean...
This work is focused on mapping biomedical datasets to a common representation, as an integral part of data harmonization for integrated biomedical da...
Automatic classification of sleep stages is one of the most important methods used for diagnostic procedures in psychiatry and neurology. This method,...
A patient-specific electromyography (EMG)-driven neuromuscular model (PENm) is developed for the potential use of human-inspired gait rehabilitation r...
This study presents the design of the recognition system that will discriminate between healthy people and people with Parkinson's disease. A diagnosi...
Background Perinatal stroke is the leading cause of hemiparetic cerebral palsy. Motor deficits and their treatment are commonly emphasized in the lite...
Technologies for scalable analysis of very large datasets have emerged in the domain of internet computing, but are still rarely used in neuroimaging ...
As shown in the literature, methods based on multiple templates usually achieve better performance, compared with those using only a single template f...
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 ...
OBJECTIVE Providing a reliable assessment of language lateralization is an important task to be performed prior to neurosurgery in patients with epile...
PURPOSE: Vitamin D status was evaluated in children with epilepsy taking anticonvulsants to determine the prevalence and risk factors of vitamin D def...
We report the case of a patient with fulminant myocarditis caused by influenza A virus, who presented with acute-onset heart failure and cardiogenic s...