Neurology

A novel EOG/EEG hybrid human-machine interface adopting eye movements and ERPs: application to robot control.

This study presents a novel human-machine interface (HMI) based on both electrooculography (EOG) and electroencephalography (EEG). This hybrid interface works in two modes: an EOG mode recognizes eye movements such as blinks, and an EEG mode detects event related potentials (ERPs) like P300. While both eye movements and ERPs have been separately used for implementing assistive interfaces, which he...

How could robotic training and botolinum toxin be combined in chronic post stroke upper limb spasticity? A pilot study.

BACKGROUND: Spasticity has a role of primary importance in functional motor recovery of upper limb after a stroke. The widespread intervention is the botulinum toxin neurolysis, however robotic training could have a role as useful addition to this conventional therapy.

Control of robotic assistance using poststroke residual voluntary effort.

Poststroke hemiparesis limits the ability to reach, in part due to involuntary muscle co-activation (synergies). Robotic approaches are being develope...

Popliteal Sciatic Nerve Block in a Pregnant Patient in the Last Trimester.

Although regional anaesthesia is a commonly preferred anaesthesia technique for pregnant patients undergoing non-obstetric surgery, peripheral nerve b...

Restoration of gait for spinal cord injury patients using HAL with intention estimator for preferable swing speed.

This paper proposes a novel gait intention estimator for an exoskeleton-wearer who needs gait support owing to walking impairment. The gait intention ...

Assist-as-Needed Robot-Aided Gait Training Improves Walking Function in Individuals Following Stroke.

A novel robot-aided assist-as-needed gait training paradigm has been developed recently. This paradigm encourages subjects' active participation durin...

Multivariate decoding of cerebral blood flow measures in a clinical model of on-going postsurgical pain.

Recent reports of multivariate machine learning (ML) techniques have highlighted their potential use to detect prognostic and diagnostic markers of pa...

Machine learning framework for early MRI-based Alzheimer's conversion prediction in MCI subjects.

Mild cognitive impairment (MCI) is a transitional stage between age-related cognitive decline and Alzheimer's disease (AD). For the effective treatmen...

Predictive Models Based on Support Vector Machines: Whole-Brain versus Regional Analysis of Structural MRI in the Alzheimer's Disease.

Decision-making systems trained on structural magnetic resonance imaging data of subjects affected by the Alzheimer's disease (AD) and healthy control...

Manifold regularized multitask feature learning for multimodality disease classification.

Multimodality based methods have shown great advantages in classification of Alzheimer's disease (AD) and its prodromal stage, that is, mild cognitive...

Using Relevance Feedback to Distinguish the Changes in EEG During Different Absence Seizure Phases.

We carried out a series of statistical experiments to explore the utility of using relevance feedback on electroencephalogram (EEG) data to distinguis...

Understanding migraine using dynamic network biomarkers.

BACKGROUND: Mathematical modeling approaches are becoming ever more established in clinical neuroscience. They provide insight that is key to understa...

Immediate repair of an incompletely transected obturator nerve during robotic-assisted pelvic lymphadenectomy.

Intraoperative injury of the obturator nerve may occur in gynecologic oncologic procedures when extensive pelvic side wall dissection is performed. In...

Electroencephalographic Changes of Brain Oscillatory Activity After Upper Limb Somatic Sensation Training in a Patient With Somatosensory Deficit After Stroke.

The development of an innovative functional assessment procedure based on the combination of electroencephalography (EEG) and robot-assisted upper lim...

A machine learning approach using auditory odd-ball responses to investigate the effect of Clozapine therapy.

OBJECTIVE: To develop a machine learning (ML) methodology based on features extracted from odd-ball auditory evoked potentials to identify neurophysio...

An assistive control approach for a lower-limb exoskeleton to facilitate recovery of walking following stroke.

This paper presents a control approach for a lower-limb exoskeleton intended to facilitate recovery of walking in individuals with lower-extremity hem...

Predictors of schizophrenia spectrum disorders in early-onset first episodes of psychosis: a support vector machine model.

Identifying early-onset schizophrenia spectrum disorders (SSD) at a very early stage remains challenging. To assess the diagnostic predictive value of...

A Neurodynamic Optimization Method for Recovery of Compressive Sensed Signals With Globally Converged Solution Approximating to l0 Minimization.

Finding the optimal solution to the constrained l0 -norm minimization problems in the recovery of compressive sensed signals is an NP-hard problem and...

Robot-assisted gait training is not superior to balance training for improving postural instability in patients with mild to moderate Parkinson's disease: a single-blind randomized controlled trial.

OBJECTIVE: The main aim was to compare robotic gait training vs. balance training for reducing postural instability in patients with Parkinson's disea...

Extrinsic finger and thumb muscles command a virtual hand to allow individual finger and grasp control.

Fine-wire intramuscular electrodes were used to obtain electromyogram (EMG) signals from six extrinsic hand muscles associated with the thumb, index, ...