Neurology

Automatic epileptic seizure detection using scalp EEG and advanced artificial intelligence techniques.

The epilepsies are a heterogeneous group of neurological disorders and syndromes characterised by recurrent, involuntary, paroxysmal seizure activity, which is often associated with a clinicoelectrical correlate on the electroencephalogram. The diagnosis of epilepsy is usually made by a neurologist but can be difficult to be made in the early stages. Supporting paraclinical evidence obtained from ...

Predicting Prodromal Alzheimer's Disease in Subjects with Mild Cognitive Impairment Using Machine Learning Classification of Multimodal Multicenter Diffusion-Tensor and Magnetic Resonance Imaging Data.

BACKGROUND: Alzheimer's disease (AD) patients show early changes in white matter (WM) structural integrity. We studied the use of diffusion tensor imaging (DTI) in assessing WM alterations in the predementia stage of mild cognitive impairment (MCI).

Neural network pattern recognition of lingual-palatal pressure for automated detection of swallow.

We describe a novel device and method for real-time measurement of lingual-palatal pressure and automatic identification of the oral transfer phase of...

A review of technological and clinical aspects of robot-aided rehabilitation of upper-extremity after stroke.

Cerebrovascular accident (CVA) or stroke is one of the leading causes of disability and loss of motor function. Millions of people around the world ar...

Discrimination of schizophrenia auditory hallucinators by machine learning of resting-state functional MRI.

Auditory hallucinations (AH) are a symptom that is most often associated with schizophrenia, but patients with other neuropsychiatric conditions, and ...

Variations of glutamate concentration within synaptic cleft in the presence of electromagnetic fields: an artificial neural networks study.

Glutamate is an excitatory neurotransmitter that is released by the majority of central nervous system synapses and is involved in developmental proce...

A comparative study of surface EMG classification by fuzzy relevance vector machine and fuzzy support vector machine.

We present a multiclass fuzzy relevance vector machine (FRVM) learning mechanism and evaluate its performance to classify multiple hand motions using ...

A Novel Method for Automated Diagnosis of Epilepsy Using Complex-Valued Classifiers.

The study reported herein proposes a new method for the diagnosis of epilepsy from electroencephalography (EEG) signals based on complex classifiers. ...

Fully Connected Cascade Artificial Neural Network Architecture for Attention Deficit Hyperactivity Disorder Classification From Functional Magnetic Resonance Imaging Data.

Automated recognition and classification of brain diseases are of tremendous value to society. Attention deficit hyperactivity disorder (ADHD) is a di...

On the role of astroglial syncytia in self-repairing spiking neural networks.

It has been shown that brain-like self-repair can arise from the interactions between neurons and astrocytes where endocannabinoids are synthesized an...

Wrist Rehabilitation Assisted by an Electromyography-Driven Neuromuscular Electrical Stimulation Robot After Stroke.

BACKGROUND: Augmented physical training with assistance from robot and neuromuscular electrical stimulation (NMES) may introduce intensive motor impro...

Decomposition of surface EMG signals from cyclic dynamic contractions.

Over the past 3 decades, various algorithms used to decompose the electromyographic (EMG) signal into its constituent motor unit action potentials (MU...

"You gotta try it all": Parents' Experiences with Robotic Gait Training for their Children with Cerebral Palsy.

AIMS: Innovative robotic technologies hold strong promise for improving walking abilities of children with cerebral palsy (CP), but may create expecta...

Robotically assisted treadmill exercise training for improving peak fitness in chronic motor incomplete spinal cord injury: A randomized controlled trial.

OBJECTIVE: To assess the effectiveness of robotically assisted body weight supported treadmill training (RABWSTT) for improving cardiovascular fitness...

RNA splicing. The human splicing code reveals new insights into the genetic determinants of disease.

To facilitate precision medicine and whole-genome annotation, we developed a machine-learning technique that scores how strongly genetic variants affe...

Bridging the gap between motor imagery and motor execution with a brain-robot interface.

According to electrophysiological studies motor imagery and motor execution are associated with perturbations of brain oscillations over spatially sim...

Kernel collaborative representation-based automatic seizure detection in intracranial EEG.

Automatic seizure detection is of great significance in the monitoring and diagnosis of epilepsy. In this study, a novel method is proposed for automa...

Molecular classification of amyotrophic lateral sclerosis by unsupervised clustering of gene expression in motor cortex.

Amyotrophic lateral sclerosis (ALS) is a rapidly progressive and ultimately fatal neurodegenerative disease, caused by the loss of motor neurons in th...

Robotic telepresence versus standardly supervised stroke alert team assessments.

BACKGROUND: Telemedicine has created access to emergency stroke care for patients in all communities, regardless of geography. We hypothesized that th...

Determining the appropriate amount of anesthetic gas using DWT and EMD combined with neural network.

The spectrum of EEG has been studied to predict the depth of anesthesia using variety of signal processing methods up to date. Those standard models h...