Latest AI and machine learning research in neurology for healthcare professionals.
Impulsivity, i.e. irresistibility in the execution of actions, may be prominent in Parkinson's disease (PD) patients who are treated with dopamine precursors or dopamine receptor agonists. In this study, we combine clinical investigations with computational modeling to explore whether impulsivity in PD patients on medication may arise as a result of abnormalities in risk, reward and punishment lea...
OBJECTIVE: This work presents a novel automated system to classify the severity of hypoxic-ischemic encephalopathy (HIE) in neonates using EEG.
Accurate muscle activity onset detection is an essential prerequisite for many applications of surface electromyogram (EMG). This study presents an un...
Focal cortical dysplasia (FCD) is the most common cause of pediatric epilepsy and the third most common lesion in adults with treatment-resistant epil...
BACKGROUND: Major psychiatric disorders are increasingly being conceptualized as 'neurodevelopmental', because they are associated with aberrant brain...
Freezing of Gait (FOG) is a frequent and disabling feature of Parkinson disease (PD). Gait rehabilitation assisted by electromechanical devices, such ...
Neuroimaging has been identified as a potentially powerful probe for the in vivo study of drug effects on the brain with utility across several phases...
OBJECTIVES/HYPOTHESIS: The objectives of this study were to describe robot-assisted sialolithotomy with sialendoscopy (RASS) for the management of lar...
Active participation and the highest level of independence during daily living are primary goals in neurorehabilitation. Therefore, standing and walki...
Recently, neuroimaging-based Alzheimer's disease (AD) or mild cognitive impairment (MCI) diagnosis has attracted researchers in the field, due to the ...
This paper presents a sparse representation and an adaptive dictionary learning based method for automated classification of multiple sclerosis (MS) l...
Robotic assistance is increasingly used in neurological rehabilitation for enhanced training. Furthermore, therapy robots have the potential for accur...
Engineered robotic fins have adapted principles of propulsion from bony-finned fish, using spatially-varying compliance and complex kinematics to prod...
Computer-aided diagnosis of dementia using a support vector machine (SVM) can be improved with feature selection. The relevance of individual features...
The outstanding locomotor and manipulation characteristics of the octopus have recently inspired the development, by our group, of multi-functional ro...
With the rapid increase of 3-dimensional (3D) content, considerable research related to the 3D human factor has been undertaken for quantitatively eva...
Autonomous poststroke rehabilitation systems which can be deployed outside hospital with no or reduced supervision have attracted increasing amount of...
The present study evaluated the diagnostic accuracy of immune system algorithms with the aim of classifying the primary types of headache that are not...
Supervised machine learning-based seizure prediction methods consider preictal period as an important prerequisite parameter during training. However,...
The quantification of non-linear characteristics of electromyography (EMG) must contain information allowing to discriminate neuromuscular strategies ...