Neurology

Detection of temporal lobe epilepsy using support vector machines in multi-parametric quantitative MR imaging.

The detection of MRI abnormalities that can be associated to seizures in the study of temporal lobe epilepsy (TLE) is a challenging task. In many cases, patients with a record of epileptic activity do not present any discernible MRI findings. In this domain, we propose a method that combines quantitative relaxometry and diffusion tensor imaging (DTI) with support vector machines (SVM) aiming to im...

Diagnostic classification of specific phobia subtypes using structural MRI data: a machine-learning approach.

While neuroimaging research has advanced our knowledge about fear circuitry dysfunctions in anxiety disorders, findings based on diagnostic groups do not translate into diagnostic value for the individual patient. Machine-learning generates predictive information that can be used for single subject classification. We applied Gaussian process classifiers to a sample of patients with specific phobia...

Upper limb robot-assisted therapy in cerebral palsy: a single-blind randomized controlled trial.

BACKGROUND: Several pilot studies have evoked interest in robot-assisted therapy (RAT) in children with cerebral palsy (CP).

Enhanced needle localization in ultrasound using beam steering and learning-based segmentation.

Segmentation of needles in ultrasound images remains a challenging problem. In this paper, we introduce a machine learning-based method for needle seg...

Ocular complications in robotic-assisted prostatectomy: a review of pathophysiology and prevention.

Ocular complications reported after robotic-assisted laparoscopic radical prostatectomy (RALP) include corneal abrasion and ischemic optic neuropathy....

Artificial neural networks in neurosurgery.

Artificial neural networks (ANNs) effectively analyze non-linear data sets. The aimed was A review of the relevant published articles that focused on ...

Epileptic seizure prediction using relative spectral power features.

OBJECTIVE: Prediction of epileptic seizures can improve the living conditions for refractory epilepsy patients. We aimed to improve sensitivity and sp...

Time-frequency modulation of ERD and EEG coherence in robot-assisted hand performance.

A better understanding of cortical modifications related to movement preparation and execution after robot-assisted training could aid in refining reh...

Decoding objects of basic categories from electroencephalographic signals using wavelet transform and support vector machines.

Decoding and classification of objects through task-oriented electroencephalographic (EEG) signals are the most crucial goals of recent researches con...

Identifying Neuroimaging Markers of Motor Disability in Acute Stroke by Machine Learning Techniques.

Conventional mass-univariate analyses have been previously used to test for group differences in neural signals. However, machine learning algorithms ...

A Randomized Controlled Trial of EEG-Based Motor Imagery Brain-Computer Interface Robotic Rehabilitation for Stroke.

Electroencephalography (EEG)-based motor imagery (MI) brain-computer interface (BCI) technology has the potential to restore motor function by inducin...

Stroke parameters identification algorithm in handwriting movements analysis by synthesis.

This paper presents a new approach to identify the stroke parameters in handwriting movement data understanding. A two-step analysis by synthesis para...

Feature Selection and Classification of Electroencephalographic Signals: An Artificial Neural Network and Genetic Algorithm Based Approach.

Feature selection is an important step in many pattern recognition systems aiming to overcome the so-called curse of dimensionality. In this study, an...

Effects of robotic therapy on upper-extremity function in children with cerebral palsy: A systematic review.

OBJECTIVE: To systematically examine the effects of robotic therapy on upper extremity (UE) function in children with cerebral palsy (CP).

Work-rate-guided exercise testing in patients with incomplete spinal cord injury using a robotics-assisted tilt-table.

PURPOSE: Robotics-assisted tilt-table (RTT) technology allows neurological rehabilitation therapy to be started early thus alleviating some secondary ...

Aggregate features in multisample classification problems.

This paper evaluates the classification of multisample problems, such as electromyographic (EMG) data, by making aggregate features available to a per...

Recovery of walking ability using a robotic device in subacute stroke patients: a randomized controlled study.

PURPOSE: This study investigates the effectiveness of Lokomat + conventional therapy in recovering walking ability in non-ambulatory subacute stroke s...

Robot-assisted gait training improves motor performances and modifies Motor Unit firing in poststroke patients.

BACKGROUND: Robotics and related technologies are realizing their promise to improve the delivery of rehabilitation therapy but the mechanism by which...

Effects of electromyography-driven robot-aided hand training with neuromuscular electrical stimulation on hand control performance after chronic stroke.

PURPOSE: An electromyography-driven robot system integrated with neuromuscular electrical stimulation (NMES) was developed to investigate its effectiv...

Latent feature representation with stacked auto-encoder for AD/MCI diagnosis.

Recently, there have been great interests for computer-aided diagnosis of Alzheimer's disease (AD) and its prodromal stage, mild cognitive impairment ...