Neurology

Decoding neural activity preceding balance loss during standing with a lower-limb exoskeleton using an interpretable deep learning model.

Falls are a leading cause of death in adults 65 and older. Recent efforts to restore lower-limb function in these populations have seen an increase in the use of wearable robotic systems; however, fall prevention measures in these systems require early detection of balance loss to be effective. Prior studies have investigated whether kinematic variables contain information about an impending fall,...

A Data-Driven Adaptive Emotion Recognition Model for College Students Using an Improved Multifeature Deep Neural Network Technology.

With the increasing pressure on college students in terms of study, work, emotion, and life, the emotional changes of college students are becoming more and more obvious. For college student management workers, if they can accurately grasp the emotional state of each college student in all aspects of the whole process, it will be of great help to student management work. The traditional way to und...

Engaging Through Awareness: Purpose-Driven Framework Development to Evaluate and Develop Future Business Strategies With Exponential Technologies Toward Healthcare Democratization.

Industry 4.0 and digital transformation will likely come with an era of changes for most manufacturers and tech industries, and even healthcare delive...

Deep learning-based classification of DSA image sequences of patients with acute ischemic stroke.

PURPOSE: Recently, a large number of patients with acute ischemic stroke benefited from the use of thrombectomy, a minimally invasive intervention tec...

A Deep Learning Method Approach for Sleep Stage Classification with EEG Spectrogram.

The classification of sleep stages is an important process. However, this process is time-consuming, subjective, and error-prone. Many automated class...

AD-CovNet: An exploratory analysis using a hybrid deep learning model to handle data imbalance, predict fatality, and risk factors in Alzheimer's patients with COVID-19.

Alzheimer's disease (AD) is the leading cause of dementia globally, with a growing morbidity burden that may exceed diagnosis and management capabilit...

A Deep Learning-Based Automatic Collateral Assessment in Patients with Acute Ischemic Stroke.

This study aimed to develop a supervised deep learning (DL) model for grading collateral status from dynamic susceptibility contrast magnetic resonanc...

Hippocampal representations for deep learning on Alzheimer's disease.

Deep learning offers a powerful approach for analyzing hippocampal changes in Alzheimer's disease (AD) without relying on handcrafted features. Nevert...

New-Onset Transient Global Amnesia: A Clinical Challenge in an Air Medical Transportation Pilot With a History of Coronavirus Disease 2019.

A 43-year-old male Bell 214C helicopter pilot presented to the emergency ward with flu-like syndrome. His nasopharyngeal severe acute respiratory synd...

The perspectives of older adults with mild cognitive impairment and their caregivers on the use of socially assistive robots in healthcare: exploring factors that influence attitude in a pre-implementation stage.

BACKGROUND: Due to increasing age and an increasing prevalence rate of neurocognitive disorders such as Mild Cognitive Impairment (MCI) and dementia, ...

Decoding the dopamine transporter imaging for the differential diagnosis of parkinsonism using deep learning.

PURPOSE: This work attempts to decode the discriminative information in dopamine transporter (DAT) imaging using deep learning for the differential di...

A Bimodal Deep Learning Architecture for EEG-fNIRS Decoding of Overt and Imagined Speech.

OBJECTIVE: Brain-computer interfaces (BCI) studies are increasingly leveraging different attributes of multiple signal modalities simultaneously. Bimo...

Estimating muscle activation from EMG using deep learning-based dynamical systems models.

. To study the neural control of movement, it is often necessary to estimate how muscles are activated across a variety of behavioral conditions. One ...

Feasibility of Overground Gait Training Using a Joint-Torque-Assisting Wearable Exoskeletal Robot in Children with Static Brain Injury.

Pediatric gait disorders are often chronic and accompanied by various complications, which challenge rehabilitation efforts. Here, we retrospectively ...

Retzius-Sparing Robot-Assisted Radical Prostatectomy.

The technique of Retzius-sparing robot-assisted radical prostatectomy (RS-RARP) and initial experience with it at a single center are provided. The te...

Early diagnosis of Alzheimer's disease based on deep learning: A systematic review.

BACKGROUND: The improvement of health indicators and life expectancy, especially in developed countries, has led to population growth and increased ag...

Spatial-frequency-temporal convolutional recurrent network for olfactory-enhanced EEG emotion recognition.

BACKGROUND: Multimedia stimulation of brain activity is important for emotion induction. Based on brain activity, emotion recognition using EEG signal...

Glaucoma diagnosis using multi-feature analysis and a deep learning technique.

In this study, we aimed to facilitate the current diagnostic assessment of glaucoma by analyzing multiple features and introducing a new cross-section...

Effects of sevoflurane versus propofol on cerebral autoregulation during anaesthesia for robot-assisted laparoscopic prostatectomy.

Robot-assisted laparoscopic prostatectomy requires a pneumoperitoneum combined with steep Trendelenburg positioning, and these conditions can be assoc...

Exemplar deep and hand-modeled features based automated and accurate cerebral hemorrhage classification method.

BACKGROUND: Cerebral hemorrhage (CH) is a commonly seen disease, and an accurate diagnosis of the type of CH is a very crucial step in treatment. Ther...