Neurology

A novel deep learning approach for classification of EEG motor imagery signals.

OBJECTIVE: Signal classification is an important issue in brain computer interface (BCI) systems. Deep learning approaches have been used successfully in many recent studies to learn features and classify different types of data. However, the number of studies that employ these approaches on BCI applications is very limited. In this study we aim to use deep learning methods to improve classificati...

Machine-learning approach identifies a pattern of gene expression in peripheral blood that can accurately detect ischaemic stroke.

Early and accurate diagnosis of stroke improves the probability of positive outcome. The objective of this study was to identify a pattern of gene expression in peripheral blood that could potentially be optimised to expedite the diagnosis of acute ischaemic stroke (AIS). A discovery cohort was recruited consisting of 39 AIS patients and 24 neurologically asymptomatic controls. Peripheral blood wa...

Robot-assisted mechanical therapy attenuates stroke-induced limb skeletal muscle injury.

The efficacy and optimization of poststroke physical therapy paradigms is challenged in part by a lack of objective tools available to researchers for...

The impact of post-stroke complications on in-hospital mortality depends on stroke severity.

INTRODUCTION: Controversies remain on whether post-stroke complications represent an independent predictor of poor outcome or just a reflection of str...

Automated quantification of three-dimensional organization of fiber-like structures in biological tissues.

Fiber-like structures are prevalent in biological tissues, yet quantitative approaches to assess their three-dimensional (3D) organization are lacking...

Detection of Mild Traumatic Brain Injury by Machine Learning Classification Using Resting State Functional Network Connectivity and Fractional Anisotropy.

Traumatic brain injury (TBI) may adversely affect a person's thinking, memory, personality, and behavior. While mild TBI (mTBI) diagnosis is challengi...

Quantitative structure-retention relationship model for the determination of naratriptan hydrochloride and its impurities based on artificial neural networks coupled with genetic algorithm.

Mathematical modeling of Quantitative Structure - Property Relationships met great interest in fields of in silico drug design and more recently, phar...

Classification of Parkinson's disease utilizing multi-edit nearest-neighbor and ensemble learning algorithms with speech samples.

BACKGROUND: The use of speech based data in the classification of Parkinson disease (PD) has been shown to provide an effect, non-invasive mode of cla...

EEG and fMRI agree: Mental arithmetic is the easiest form of imagery to detect.

fMRI and EEG during mental imagery provide alternative methods of detecting awareness in patients with disorders of consciousness (DOC) without relian...

Quantitative EEG Evaluation During Robot-Assisted Foot Movement.

Passiveand imagined limbmovements induce changes in cerebral oscillatory activity. Central modulatory effects play a role in plastic changes, and are ...

Using robot fully assisted functional movements in upper-limb rehabilitation of chronic stroke patients: preliminary results.

BACKGROUND: Robotic rehabilitation is promising to promote function in stroke patients. The assist as needed training paradigm has shown to stimulate ...

Adequate tacrolimus concentration for myasthenia gravis treatment.

BACKGROUND AND PURPOSE: A single, oral dose of 3 mg/day tacrolimus, approved for myasthenia gravis (MG) treatment in Japan, was shown to reduce steroi...

Scale-Dependent Signal Identification in Low-Dimensional Subspace: Motor Imagery Task Classification.

Motor imagery electroencephalography (EEG) has been successfully used in locomotor rehabilitation programs. While the noise-assisted multivariate empi...

Impact of Cognitive Loading on Postural Control in Parkinson's Disease With Freezing of Gait.

To assess standing balance in Parkinson's disease (PD) patients with and without freezing of gait (FOG) during cognitive loading. A balance assessment...

Robotic quantification of upper extremity loss of independent joint control or flexion synergy in individuals with hemiparetic stroke: a review of paradigms addressing the effects of shoulder abduction loading.

Unsupported or "against-gravity" reaching and hand opening movements are greatly impaired in individuals with hemiparetic stroke. The reduction in rea...

Procalcitonin as a potential predicting factor for prognosis in bacterial meningitis.

We investigated the potential role of serum procalcitonin in differentiating bacterial meningitis from viral meningitis, and in predicting the prognos...

An EEG-based machine learning method to screen alcohol use disorder.

Screening alcohol use disorder (AUD) patients has been challenging due to the subjectivity involved in the process. Hence, robust and objective method...

A neural network model for visual selection and shifting.

In this paper, a two-layer network is built to simulate the mechanism of visual selection and shifting based on the mapping dynamic model for instanta...

An Angstrom-sensitive, differential MEMS capacitor for monitoring the milliliter dynamics of fluids.

A device, with MEMS sensors at its core, has been fabricated and tested for measuring low fluid pressure and slow flow rates. The motivation was to me...

Can a Soft Robotic Probe Use Stiffness Control Like a Human Finger to Improve Efficacy of Haptic Perception?

When humans are asked to palpate a soft tissue to locate a hard nodule, they regulate the stiffness, speed, and force of the finger during examination...