Fibromyalgia

The role of robot-assisted training on rehabilitation outcomes in Parkinson's disease: a systematic review and meta-analysis.

PURPOSE: The study aims to assess the efficacy of robot-assisted rehabilitation training on upper and lower limb motor function and fatigue in Parkinson's disease (PD), and to explore the best-acting robotic rehabilitation program.

A robot-based interception task to quantify upper limb impairments in proprioceptive and visual feedback after stroke.

BACKGROUND: A key motor skill is the ability to rapidly interact with our dynamic environment. Humans can generate goal-directed motor actions in response to sensory stimulus within ~ 60-200ms. This ability can be impaired after stroke, but most clinical tools lack any measures of rapid feedback processing. Reaching tasks have been used as a framework to quantify impairments in generating motor co...

Investigation of the mechanism of action of deep brain stimulation for the treatment of Parkinson's disease.

Parkinson's disease (PD) is a severe, progressive, neurological disorder. PD is not a single disease, but rather resembles a syndrome. PD includes two...

Deep Learning for Detecting Multi-Level Driver Fatigue Using Physiological Signals: A Comprehensive Approach.

A large share of traffic accidents is related to driver fatigue. In recent years, many studies have been organized in order to diagnose and warn drive...

The Effect of Using a Rehabilitation Robot for Patients with Post-Coronavirus Disease (COVID-19) Fatigue Syndrome.

The aim of this study was to compare the effectiveness of traditional neurological rehabilitation and neurological rehabilitation combined with a reha...

A synthetic data generation system for myalgic encephalomyelitis/chronic fatigue syndrome questionnaires.

Artificial intelligence or machine-learning-based models have proven useful for better understanding various diseases in all areas of health science. ...

Self-Attentive Channel-Connectivity Capsule Network for EEG-Based Driving Fatigue Detection.

Deep neural networks have recently been successfully extended to EEG-based driving fatigue detection. Nevertheless, most existing models fail to revea...

A Novel Approach to Detecting Muscle Fatigue Based on sEMG by Using Neural Architecture Search Framework.

Muscle fatigue detection is of great significance to human physiological activities, but many complex factors increase the difficulty of this task. In...

Applying a Smartwatch to Predict Work-related Fatigue for Emergency Healthcare Professionals: Machine Learning Method.

INTRODUCTION: Healthcare professionals frequently experience work-related fatigue, which may jeopardize their health and put patient safety at risk. I...

COVID-19 symptom identification using Deep Learning and hardware emulated systems.

The COVID-19 pandemic disrupted regular global activities in every possible way. This pandemic, caused by the transmission of the infectious Coronavir...

EEG motor imagery classification using deep learning approaches in naïve BCI users.

Motor Imagery (MI)-Brain Computer-Interfaces (BCI) illiteracy defines that not all subjects can achieve a good performance in MI-BCI systems due to di...

Deep learning supported machine vision system to precisely automate the wild blueberry harvester header.

An operator of a wild blueberry harvester faces the fatigue of manually adjusting the height of the harvester's head, considering spatial variations i...

A Product Fuzzy Convolutional Network for Detecting Driving Fatigue.

Existing driving fatigue detection methods rarely consider how to effectively fuse the advantages of the electroencephalogram (EEG) and electrocardiog...

Evaluation of a machine-learning-driven active-passive upper-limb exoskeleton robot: Experimental human-in-the-loop study.

Evaluating exoskeleton actuation methods and designing an effective controller for these exoskeletons are both challenging and time-consuming tasks. T...

Weakly Supervised Classification of Vital Sign Alerts as Real or Artifact.

A significant proportion of clinical physiologic monitoring alarms are false. This often leads to alarm fatigue in clinical personnel, inevitably comp...

Adrenal lesion classification with abdomen caps and the effect of ROI size.

Accurate classification of adrenal lesions on magnetic resonance (MR) images are very important for diagnosis and treatment planning. The detection an...

A hybrid orthosis combining functional electrical stimulation and soft robotics for improved assistance of drop-foot.

Drop-foot is characterised by an inability to lift the foot, and affects an estimated 3 million people worldwide. Current treatment methods include ri...

Restorative perception of urban streets: Interpretation using deep learning and MGWR models.

Restorative environments help people recover from mental fatigue and negative emotional and physical reactions to stress. Excellent restorative enviro...

Bioinspired Liquid Crystalline Spinning Enables Scalable Fabrication of High-Performing Fibrous Artificial Muscles.

Leveraging liquid crystal elastomers (LCEs) to realize scalable fabrication of high-performing fibrous artificial muscles is of particular interest be...

Spinal disease diagnosis assistant based on MRI images using deep transfer learning methods.

INTRODUCTION: In light of the potential problems of missed diagnosis and misdiagnosis in the diagnosis of spinal diseases caused by experience differe...