Geriatrics

Voice-Controlled Intelligent Personal Assistants to Support Aging in Place.

BACKGROUND/OBJECTIVES: Many older adults wish to age in place, and voice-controlled intelligent personal assistants (VIPAs; eg, Amazon Echo and Google Home) potentially could support unmet home needs. No prior studies have researched the real-world use of VIPAs among older adults. We sought to explore how older adults and caregivers utilize VIPAs.

Hippocampal segmentation for brains with extensive atrophy using three-dimensional convolutional neural networks.

Hippocampal volumetry is a critical biomarker of aging and dementia, and it is widely used as a predictor of cognitive performance; however, automated hippocampal segmentation methods are limited because the algorithms are (a) not publicly available, (b) subject to error with significant brain atrophy, cerebrovascular disease and lesions, and/or (c) computationally expensive or require parameter t...

Granger causality analysis in combination with directed network measures for classification of MS patients and healthy controls using task-related fMRI.

Several studies have already assessed brain network variations in multiple sclerosis (MS) patients and healthy controls (HCs). The underlying neural s...

Identification and Quantification of Cardiovascular Structures From CCTA: An End-to-End, Rapid, Pixel-Wise, Deep-Learning Method.

OBJECTIVES: This study designed and evaluated an end-to-end deep learning solution for cardiac segmentation and quantification.

Adaptive Neural Sliding-Mode Controller for Alternative Control Strategies in Lower Limb Rehabilitation.

Research on control strategies for rehabilitation robots has gradually shifted from providing therapies with fixed, relatively stiff assistance to com...

Fetal Congenital Heart Disease Echocardiogram Screening Based on DGACNN: Adversarial One-Class Classification Combined with Video Transfer Learning.

Fetal congenital heart disease (FHD) is a common and serious congenital malformation in children. In Asia, FHD birth defect rates have reached as high...

Companion robots for older people: importance of user-centred design demonstrated through observations and focus groups comparing preferences of older people and roboticists in South West England.

OBJECTIVE: Companion robots, such as Paro, may reduce agitation and depression for older people with dementia. However, contradictory research outcome...

BIA: ehavior dentification lgorithm Using Unsupervised Learning Based on Sensor Data for Home Elderly.

Behavior identification plays an important role in supporting homecare for the elderly living alone. In literature, plenty of algorithms have been des...

Developing assistive robots for people with mild cognitive impairment and mild dementia: a qualitative study with older adults and experts in aged care.

OBJECTIVES: This research is part of an international project to design and test a home-based healthcare robot to help older adults with mild cognitiv...

Individualized prediction of depressive disorder in the elderly: A multitask deep learning approach.

INTRODUCTION: Depressive disorder is one of the major public health problems among the elderly. An effective depression risk prediction model can prov...

Artificial neural network to estimate micro-architectural properties of cortical bone using ultrasonic attenuation: A 2-D numerical study.

The goal of this study is to estimate micro-architectural parameters of cortical porosity such as pore diameter (φ), pore density (ρ) and porosity (ν)...

Using path signatures to predict a diagnosis of Alzheimer's disease.

The path signature is a means of feature generation that can encode nonlinear interactions in data in addition to the usual linear terms. It provides ...

Identification of Vertebral Fractures by Convolutional Neural Networks to Predict Nonvertebral and Hip Fractures: A Registry-based Cohort Study of Dual X-ray Absorptiometry.

Background Detection of vertebral fractures (VFs) aids in management of osteoporosis and targeting of fracture prevention therapies. Purpose To determ...

EUSKOR: End-to-end coreference resolution system for Basque.

This paper describes the process of adapting the Stanford Coreference resolution module to the Basque language, taking into account the characteristic...

CIGuide: in situ augmented reality laser guidance.

PURPOSE : A robotic intraoperative laser guidance system with hybrid optic-magnetic tracking for skull base surgery is presented. It provides in situ ...

Using supervised learning machine algorithm to identify future fallers based on gait patterns: A two-year longitudinal study.

INTRODUCTION: Given their major health consequences in the elderly, identifying people at risk of fall is a major challenge faced by clinicians. A lot...

Quantifying brain metabolism from FDG-PET images into a probability of Alzheimer's dementia score.

F-fluorodeoxyglucose positron emission tomography (FDG-PET) enables in-vivo capture of the topographic metabolism patterns in the brain. These images...

Deep Learning to Improve Breast Cancer Detection on Screening Mammography.

The rapid development of deep learning, a family of machine learning techniques, has spurred much interest in its application to medical imaging probl...

Detection of Human Fall Using Floor Vibration and Multi-Features Semi-Supervised SVM.

Human falls are the premier cause of fatal and nonfatal injuries among older adults. The health outcome of a fall event is largely dependent on rapid ...

Estimation of Vertical Ground Reaction Force Using Low-Cost Insole With Force Plate-Free Learning From Single Leg Stance and Walking.

For the evaluation of pathological gait, a machine learning-based estimation of the vertical ground reaction force (vGRF) using a low-cost insole is p...