Neurology

Prediction of brain age suggests accelerated atrophy after traumatic brain injury.

OBJECTIVE: The long-term effects of traumatic brain injury (TBI) can resemble observed in normal ageing, suggesting that TBI may accelerate the ageing process. We investigate this using a neuroimaging model that predicts brain age in healthy individuals and then apply it to TBI patients. We define individuals' differences in chronological and predicted structural "brain age," and test whether TBI ...

[Artificial intelligence meeting neuropsychology. Semantic memory in normal and pathological aging].

Artificial intelligence (IA) is the subject of much research, but also many fantasies. It aims to reproduce human intelligence in its learning capacity, knowledge storage and computation. In 2014, the Defense Advanced Research Projects Agency (DARPA) started the restoring active memory (RAM) program that attempt to develop implantable technology to bridge gaps in the injured brain and restore norm...

[Exoskeletons for rehabilitation of patients with spinal cord injuries. Options and limitations].

BACKGROUND: Mobile exoskeletons are increasingly being applied in the course of rehabilitation and provision of medical aids to patients with spinal c...

Clinical prediction from structural brain MRI scans: a large-scale empirical study.

Multivariate pattern analysis (MVPA) methods have become an important tool in neuroimaging, revealing complex associations and yielding powerful predi...

Defining multivariate normative rules for healthy aging using neuroimaging and machine learning: an application to Alzheimer's disease.

BACKGROUND: Neuroimaging techniques combined with computational neuroanatomy have been playing a role in the investigation of healthy aging and Alzhei...

Towards an expert system for accurate diagnosis and progress monitoring of Parkinson's disease.

While Parkinson's disease is a chronic and progressive movement disorder, no one can predict which symptoms will affect an individual patient. At the ...

Chat-Bots for People with Parkinson's Disease: Science Fiction or Reality?

People with Parkinson's disease are known to have difficulties in language and communication. This paper proposes the use of an artificial conversatio...

Prediction of Longitudinal Development of Infant Cortical Surface Shape Using a 4D Current-Based Learning Framework.

Understanding the early dynamics of the highly folded human cerebral cortex is still an actively evolving research field teeming with unanswered quest...

Neuropsychological test selection for cognitive impairment classification: A machine learning approach.

INTRODUCTION: Reducing the amount of testing required to accurately detect cognitive impairment is clinically relevant. The aim of this research was t...

Applying Automated MR-Based Diagnostic Methods to the Memory Clinic: A Prospective Study.

Several studies have demonstrated that fully automated pattern recognition methods applied to structural magnetic resonance imaging (MRI) aid in the d...

Identification of Conversion from Normal Elderly Cognition to Alzheimer's Disease using Multimodal Support Vector Machine.

Alzheimer's disease (AD) is one of the most serious progressive neurodegenerative diseases among the elderly, therefore the identification of conversi...

Nonholonomic mobile system control by combining EEG-based BCI with ANFIS.

Motor imagery EEG-based BCI has advantages in the assistance of human control of peripheral devices, such as the mobile robot or wheelchair, because t...

Improved walking ability with wearable robot-assisted training in patients suffering chronic stroke.

Wearable robotic devices provide safe and intensive rehabilitation, enabling repeated motions for motor function recovery in stroke patients. The aim ...

Application of multi-output support vector regression on EMGs to decode hand continuous movement trajectory.

Applications of neural machine interfaces have received increased attention during the last decades. It is crucial to realize the continuous control o...

Do post-stroke patients benefit from robotic verticalization? A pilot-study focusing on a novel neurophysiological approach.

BACKGROUND: Tilt-table equipped with the dynamic foot-support (ERIGO) and the functional electric stimulation could be a safe and suitable device for ...

Novel images extraction model using improved delay vector variance feature extraction and multi-kernel neural network for EEG detection and prediction.

BACKGROUND: Advanced intelligent methodologies could help detect and predict diseases from the EEG signals in cases the manual analysis is inefficient...

Combined effects of transcranial direct current stimulation (tDCS) and transcutaneous spinal direct current stimulation (tsDCS) on robot-assisted gait training in patients with chronic stroke: A pilot, double blind, randomized controlled trial.

PURPOSE: Preliminary evidence has shown no additional effects of transcranial direct current stimulation (tDCS) on robotic gait training in chronic st...

Robot-assisted training to improve proprioception does benefit from added vibro-tactile feedback.

Proprioception is central for motor control and its role must also be taken into account when designing motor rehabilitation training protocols. This ...

Semi-supervised manifold learning with affinity regularization for Alzheimer's disease identification using positron emission tomography imaging.

Dementia, Alzheimer's disease (AD) in particular is a global problem and big threat to the aging population. An image based computer-aided dementia di...

Tuning of robotic therapy controllers for stroke gait: Using isometrically constrained EMG modular structures.

The development of EMG based controllers for automated gait orthosis is a promising intervention for post-stroke gait rehabilitation and assistive dev...