AIMC Topic: Accidental Falls

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Acceleration Magnitude at Impact Following Loss of Balance Can Be Estimated Using Deep Learning Model.

Sensors (Basel, Switzerland) Oct 28, 2020
Pre-impact fall detection can detect a fall before a body segment hits the ground. When it is integrated with a protective system, it can directly prevent an injury due to hitting the ground. An impact acceleration peak magnitude is one of key measur...
Deep Learning Accidental Falls Wearable Electronic Devices Acceleration Humans
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Detection of Gait Abnormalities for Fall Risk Assessment Using Wrist-Worn Inertial Sensors and Deep Learning.

Sensors (Basel, Switzerland) Sep 19, 2020
Falls are a significant threat to the health and independence of elderly people and represent an enormous burden on the healthcare system. Successfully predicting falls could be of great help, yet this requires a timely and accurate fall risk assessm...
Wearable Electronic Devices Wrist Gait Analysis Humans Deep Learning Accidental Falls Aged Risk Assessment
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Automatic fall detection using region-based convolutional neural network.

International journal of injury control and safety promotion Sep 15, 2020
The common classifiers usually used to detect fall incidents depend on building and maintaining complex feature extraction for accurate machine learning tasks. However, these efforts have not succeeded in determining an ideal classifier or feature ex...
Humans Neural Networks, Computer Machine Learning Accidental Falls Image Processing, Computer-Assisted Monitoring, Ambulatory
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Application of Machine Learning Methods in Nursing Home Research.

International journal of environmental research and public health Aug 27, 2020
A machine learning (ML) system is able to construct algorithms to continue improving predictions and generate automated knowledge through data-driven predictors or decisions. Objective: The purpose of this study was to compare six ML methods (random...
Activities of Daily Living Nursing Homes Nursing Research Humans Machine Learning Algorithms Accidental Falls Support Vector Machine Female Male
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Using Machine Learning to Make Predictions in Patients Who Fall.

The Journal of surgical research Aug 18, 2020
BACKGROUND: As the population ages, the incidence of traumatic falls has been increasing. We hypothesize that a machine learning algorithm can more accurately predict mortality after a fall compared with a standard logistic regression (LR) model base...
Humans Machine Learning Algorithms Retrospective Studies Aged, 80 and over Adult Male Middle Aged Intensive Care Units Female Aged Trauma Centers Glasgow Coma Scale Decision Trees Patient Discharge Injury Severity Score Length of Stay Accidental Falls ROC Curve
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Development and validation of a robotic multifactorial fall-risk predictive model: A one-year prospective study in community-dwelling older adults.

PloS one Jun 25, 2020
BACKGROUND: Falls in the elderly are a major public health concern because of their high incidence, the involvement of many risk factors, the considerable post-fall morbidity and mortality, and the health-related and social costs. Given that many fal...
Independent Living Risk Assessment Accidental Falls Incidence Geriatric Assessment Aged Walking Speed Aged, 80 and over Robotics Male Humans Postural Balance Prospective Studies Female
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Rehabilitation of older people with Parkinson's disease: an innovative protocol for RCT study to evaluate the potential of robotic-based technologies.

BMC neurology May 13, 2020
BACKGROUND: Parkinson's disease is one of the most frequent causes of disability among the older adults. It is a chronic-progressive neuro-degenerative disease, characterized by several motor disorders. Balance disorders are a symptom that involves t...
Sensation Disorders Single-Blind Method Exercise Therapy Gait Disorders, Neurologic Randomized Controlled Trials as Topic Humans Robotics Postural Balance Aged, 80 and over Male Accidental Falls Parkinson Disease Research Design Female Aged
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Deep learning prediction of falls among nursing home residents with Alzheimer's disease.

Geriatrics & gerontology international Apr 8, 2020
AIM: This study aimed to use a convolutional neural network (CNN) to investigate the associations between the time of falling and multiple complicating factors, including age, dementia severity, lower extremity strength and physical function, among n...
Aged, 80 and over Male Severity of Illness Index Cohort Studies Lower Extremity Nursing Homes Deep Learning Homes for the Aged Accidental Falls Mental Status and Dementia Tests Prospective Studies Muscle Strength Female Geriatric Assessment Risk Factors Alzheimer Disease Aged Humans
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Characteristic analysis and fuzzy simulation of falls-from-height mechanics, and case studies.

Forensic science international Apr 7, 2020
In this paper, methods for scientifically inferring the causes of the falls-from-height accidents, that is, the initial fall postures, and reconstructing the fall accident are presented. For this purpose, the general types of fall were subdivided int...
Humans Computer Simulation Accidental Falls Fuzzy Logic Reproducibility of Results Biomechanical Phenomena Posture Forensic Sciences
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Utilizing artificial intelligence for falls management in memory care.

Geriatric nursing (New York, N.Y.) Mar 25, 2020
Accidental Falls Memory Disorders Humans Artificial Intelligence
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