Neurology

Monitoring Active Patient Participation During Robotic Rehabilitation: Comparison Between a Robot-Based Metric and an EMG-Based Metric.

While rehabilitation robots present a much-needed solution to improving early mobilization therapy in demanding clinical settings, they also present new challenges and opportunities in patient monitoring. Aside from the fundamental challenge of quantifying a patient's voluntary contribution during robot-led therapy motion, many sensors cannot be used in clinical settings due to time and space limi...

A machine learning approach for computation of cardiovascular intrinsic frequencies.

Analysis of cardiovascular waveforms provides valuable clinical information about the state of health and disease. The intrinsic frequency (IF) method is a recently introduced framework that uses a single arterial pressure waveform to extract physiologically relevant information about the cardiovascular system. The clinical usefulness and physiological accuracy of the IF method have been well-esta...

Deep learning visual field global index prediction with optical coherence tomography parameters in glaucoma patients.

The aim of this study was to predict three visual filed (VF) global indexes, mean deviation (MD), pattern standard deviation (PSD), and visual field i...

Solitary Fibrous Tumor of the Prostate Treated with Frozen-Section Supported Robot-Assisted Nerve-Sparing Radical Prostatectomy.

INTRODUCTION: Solitary fibrous tumors (SFTs) of the prostate are extremely rare. We report on a 60-year-old man who was diagnosed with prostatic SFT t...

An advanced approach for the electrical responses of discrete fractional-order biophysical neural network models and their dynamical responses.

The multiple activities of neurons frequently generate several spiking-bursting variations observed within the neurological mechanism. We show that a ...

Cholesterol Levels, Hormone Replacement Therapy, and Incident Dementia among Older Adult Women.

Previous studies revealed that hormone replacement therapy (HRT) probably has a protective effect for preventing dementia in post-menopausal women. Ho...

Depressive Disorder Recognition Based on Frontal EEG Signals and Deep Learning.

Depressive disorder (DD) has become one of the most common mental diseases, seriously endangering both the affected person's psychological and physica...

Next-generation cognitive assessment: Combining functional brain imaging, system perturbations and novel equipment interfaces.

Conventional cognitive assessment is widely used in clinical and research settings, in educational institutions, and in the corporate world for person...

Surgical skill level classification model development using EEG and eye-gaze data and machine learning algorithms.

The aim of this study was to develop machine learning classification models using electroencephalogram (EEG) and eye-gaze features to predict the leve...

Hybrid Robotic and Electrical Stimulation Assistance Can Enhance Performance and Reduce Mental Demand.

Combining functional electrical stimulation (FES) and robotics may enhance recovery after stroke, by providing neural feedback with the former while i...

Retina Oculomics in Neurodegenerative Disease.

Ophthalmic biomarkers have long played a critical role in diagnosing and managing ocular diseases. Oculomics has emerged as a field that utilizes ocul...

A Concentric Tube Steerable Drilling Robot for Minimally Invasive Spinal Fixation of Osteoporotic Vertebrae.

Spinal fixation with rigid pedicle screws have shown to be an effective treatment for many patients. However, this surgical option has been proved to ...

Quality of life after non-nerve-sparing, robot-assisted radical prostatectomy.

OBJECTIVE: To evaluate quality of life (QOL) after non-nerve-sparing, robot-assisted radical prostatectomy (RARP) and factors associated with worsened...

Plasma interleukin 6 as an outcome predictor of traumatic brain injury patients.

Traumatic brain injury is one of the leading causes of death and disability in young adults. Previous studies have suggested that neuroinflammatory pr...

Neural prosthesis control restores near-normative neuromechanics in standing postural control.

Current lower-limb prostheses do not provide active assistance in postural control tasks to maintain the user's balance, particularly in situations of...

An empirical comparison of deep learning explainability approaches for EEG using simulated ground truth.

Recent advancements in machine learning and deep learning (DL) based neural decoders have significantly improved decoding capabilities using scalp ele...

Deep-learning segmentation method for optical coherence tomography angiography in ophthalmology.

PURPOSE: The optic disc and the macular are two major anatomical structures in the human eye. Optic discs are associated with the optic nerve. Macular...

Deep learning based diagnosis of Alzheimer's disease using FDG-PET images.

PURPOSE: The aim of this study is to develop a deep neural network to diagnosis Alzheimer's disease and categorize the stages of the disease using FDG...

Deep learning based on susceptibility-weighted MR sequence for detecting cerebral microbleeds and classifying cerebral small vessel disease.

BACKGROUND: Cerebral microbleeds (CMBs) serve as neuroimaging biomarkers to assess risk of intracerebral hemorrhage and diagnose cerebral small vessel...

Characterisation of Cognitive Load Using Machine Learning Classifiers of Electroencephalogram Data.

A high cognitive load can overload a person, potentially resulting in catastrophic accidents. It is therefore important to ensure the level of cogniti...