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Accidental Falls

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Land-walking vs. water-walking interventions in older adults: Effects on aerobic fitness.

Journal of sport and health science
BACKGROUND: Low cardiorespiratory fitness is an independent predictor of all-cause and cardiovascular mortality, and interventions that increase fitness reduce risk. Water-walking decreases musculoskeletal impact and risk of falls in older individual...

Deep Learning for Fall Risk Assessment With Inertial Sensors: Utilizing Domain Knowledge in Spatio-Temporal Gait Parameters.

IEEE journal of biomedical and health informatics
Fall risk assessment is essential to predict and prevent falls in geriatric populations, especially patients with life-long conditions like neurological disorders. Inertial sensor-based pervasive gait analysis systems have become viable means to faci...

Wearable Fall Detector Using Recurrent Neural Networks.

Sensors (Basel, Switzerland)
Falls have become a relevant public health issue due to their high prevalence and negative effects in elderly people. Wearable fall detector devices allow the implementation of continuous and ubiquitous monitoring systems. The effectiveness for analy...

Fall Risk Prediction in Multiple Sclerosis Using Postural Sway Measures: A Machine Learning Approach.

Scientific reports
Numerous postural sway metrics have been shown to be sensitive to balance impairment and fall risk in individuals with MS. Yet, there are no guidelines concerning the most appropriate postural sway metrics to monitor impairment. This investigation im...

A vision-based approach for fall detection using multiple cameras and convolutional neural networks: A case study using the UP-Fall detection dataset.

Computers in biology and medicine
The automatic recognition of human falls is currently an important topic of research for the computer vision and artificial intelligence communities. In image analysis, it is common to use a vision-based approach for fall detection and classification...

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

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Research on control strategies for rehabilitation robots has gradually shifted from providing therapies with fixed, relatively stiff assistance to compelling alternatives with assistance or challenge strategies to maximize subject participation. Thes...

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

Experimental gerontology
INTRODUCTION: Given their major health consequences in the elderly, identifying people at risk of fall is a major challenge faced by clinicians. A lot of studies have confirmed the relationships between gait parameters and falls incidence. However, a...

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

Sensors (Basel, Switzerland)
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 response and rescue of the fallen elder. Being able to provide an accurate and fast fall detection w...

Development and validation of a pragmatic natural language processing approach to identifying falls in older adults in the emergency department.

BMC medical informatics and decision making
BACKGROUND: Falls among older adults are both a common reason for presentation to the emergency department, and a major source of morbidity and mortality. It is critical to identify fall patients quickly and reliably during, and immediately after, em...

A New Approach to Fall Detection Based on Improved Dual Parallel Channels Convolutional Neural Network.

Sensors (Basel, Switzerland)
Falls are the major cause of fatal and non-fatal injury among people aged more than 65 years. Due to the grave consequences of the occurrence of falls, it is necessary to conduct thorough research on falls. This paper presents a method for the study ...