AIMC Topic: Accidental Falls
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A comparison of accuracy of fall detection algorithms (threshold-based vs. machine learning) using waist-mounted tri-axial accelerometer signals from a comprehensive set of falls and non-fall trials.
Medical & biological engineering & computing
Apr 22, 2016
Falls are the leading cause of injury-related morbidity and mortality among older adults. Over 90 % of hip and wrist fractures and 60 % of traumatic brain injuries in older adults are due to falls. Another serious consequence of falls among older adu...
MIT-Skywalker: A Novel Gait Neurorehabilitation Robot for Stroke and Cerebral Palsy.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Feb 25, 2016
The MIT-Skywalker is a novel robotic device developed for the rehabilitation or habilitation of gait and balance after a neurological injury. It represents an embodiment of the concept exhibited by passive walkers for rehabilitation training. Its nov...
Classification of radiology reports for falls in an HIV study cohort.
Journal of the American Medical Informatics Association : JAMIA
Nov 13, 2015
OBJECTIVE: To identify patients in a human immunodeficiency virus (HIV) study cohort who have fallen by applying supervised machine learning methods to radiology reports of the cohort.
Fall Down Detection Under Smart Home System.
Journal of medical systems
Aug 15, 2015
Medical technology makes an inevitable trend for the elderly population, therefore the intelligent home care is an important direction for science and technology development, in particular, elderly in-home safety management issues become more and mor...
Tandem Stance Avoidance Using Adaptive and Asymmetric Admittance Control for Fall Prevention.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
May 4, 2015
Fall prevention is one of the most important functions of walking assistance devices for user's safety. It is preferable that these devices prevent the user from being in the state where the risk of falling is high rather than helping them recovering...
Touch
Gait Disorders, Neurologic
Physical Stimulation
Canes
Aged
Exoskeleton Device
Aged, 80 and over
Man-Machine Systems
Male
Self-Help Devices
Accidental Falls
Models, Biological
Humans
Monitoring, Ambulatory
Computer Simulation
Robotics
Stress, Mechanical
Female
Equipment Design
Equipment Failure Analysis
Walking
Gait
Artificial neural network and falls in community-dwellers: a new approach to identify the risk of recurrent falling?
Journal of the American Medical Directors Association
Oct 29, 2014
BACKGROUND: Identification of the risk of recurrent falls is complex in older adults. The aim of this study was to examine the efficiency of 3 artificial neural networks (ANNs: multilayer perceptron [MLP], modified MLP, and neuroevolution of augmenti...
An Advanced Self-Similarity Measure: Average of Level-Pairwise Hurst Exponent Estimates (ALPHEE).
IEEE transactions on bio-medical engineering
Aug 1, 2025
Many natural processes are characterized by complex patterns of self-similarity, where repetitive structures occur across different resolutions. The Hurst exponent is a key parameter used to quantify this self-similarity. While wavelet-based techniqu...
Optimization enabled ensemble based deep learning model for elderly falling risk prediction.
Computer methods in biomechanics and biomedical engineering
Jul 1, 2025
Predicting fall risk in the elderly is crucial for enhancing safety and well-being. Aging and chronic diseases often impair balance, increasing fall risk. This study aims to develop an advanced fall risk prediction model using an optimized deep learn...
Aging With Artificial Intelligence: How Technology Enhances Older Adults' Health and Independence.
The journals of gerontology. Series A, Biological sciences and medical sciences
Jun 10, 2025
BACKGROUND: As the global population ages healthcare challenges are escalating. Frailty, a clinical syndrome characterized by decreased reserve and resilience to stressors, is critically linked to adverse health outcomes in older adults. However, art...
Posture analysis in predicting fall-related injuries during French Navy Special Forces selection course using machine learning: a proof-of-concept study.
BMJ military health
May 21, 2025
INTRODUCTION: Injuries induced by falls represent the main cause of failure in the French Navy Special Forces selection course. In the present study, we made the assumption that probing the posture might contribute to predicting the risk of fall-rela...
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