AIMC Topic: Accidental Falls

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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...
Self-Help Devices Touch Gait Disorders, Neurologic Physical Stimulation Canes Equipment Failure Analysis Humans Exoskeleton Device Man-Machine Systems Models, Biological Computer Simulation Monitoring, Ambulatory Female Stress, Mechanical Aged Robotics Aged, 80 and over Walking Equipment Design Male Gait Accidental Falls
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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...
Aged Sex Factors Humans Recurrence Neural Networks, Computer Cross-Sectional Studies Age Factors Aged, 80 and over Independent Living Accidental Falls Female Male Sensitivity and Specificity Incidence Geriatric Assessment Risk Assessment
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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...
Deep Learning Accidental Falls Risk Factors Aged Neural Networks, Computer Risk Assessment Algorithms Humans
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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...
Humans Artificial Intelligence Accidental Falls Wearable Electronic Devices Independent Living Wireless Technology Aged Aging Quality of Life
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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...
Posture Postural Balance Military Personnel France Male Humans Risk Assessment Machine Learning Accidental Falls Adult
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Comparing interpretable machine learning models for fall risk in middle-aged and older adults with and without pain.

Scientific reports May 16, 2025
Pain is common in middle-aged and older adults, has also been identified as a fall risk factor, whereas the mechanism of falls in pain is unclear. This study included 13,074 middle-aged and older adults from the China health and retirement longitudin...
Risk Factors Aged Aged, 80 and over Male Humans Machine Learning Female Accidental Falls Logistic Models Longitudinal Studies Pain Middle Aged Risk Assessment China
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Machine Learning Scoring Reveals Increased Frequency of Falls Proximal to Death in Drosophila melanogaster.

The journals of gerontology. Series A, Biological sciences and medical sciences May 5, 2025
Falls are a significant cause of human disability and death. Risk factors include normal aging, neurodegenerative disease, and sarcopenia. Drosophila melanogaster is a powerful model for study of normal aging and for modeling human neurodegenerative ...
Machine Learning Animals Video Recording Drosophila melanogaster Aging Accidental Falls
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Development of an Assistance Robot for Fall Detection and Reporting in Healthcare.

Studies in health technology and informatics May 2, 2025
Falls pose a substantial risk to elderly individuals, especially those over 65, often leading to severe consequences. This project investigates the potential of the tēmi robot for fall detection in care facilities and its integration into a simulated...
Robotics Equipment Design Equipment Failure Analysis Humans Monitoring, Ambulatory Accidental Falls
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Machine Learning Predicts Risk of Falls in Parkison's Disease Patients in a Multicenter Observational Study.

European journal of neurology May 1, 2025
BACKGROUND: Postural instability and gait difficulties are key symptoms of Parkinson's disease (PD), elevating the risk of falls substantially. Falls afflict 35% to 90% of PD patients, representing a major challenge in managing the condition. Accurat...
Italy Machine Learning Accidental Falls Female Cohort Studies Parkinson Disease Humans Aged Male Middle Aged
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Automated Fall Detection in Smart Homes Using Multiple Radars and Machine Learning Classifiers.

Studies in health technology and informatics Apr 8, 2025
Falls pose a significant risk, especially among elderly persons. Recently, radar sensors have been explored for fall detection. In this study, an attempt has been made to classify fall detection using multiple radars, machine learning (ML) classifier...
Humans Machine Learning Monitoring, Ambulatory Aged Radar Accidental Falls Support Vector Machine
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