AIMC Topic: Accidental Falls

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Fatal fall from a height: is it possible to apply artificial intelligence techniques for height estimation?

International journal of legal medicine Dec 7, 2024
Fall from a height trauma is characterized by a multiplicity of injuries, related to multiple factors. The height of the fall is the factor that most influences the kinetic energy of the body and appears to be one of the factors that most affects the...
Linear Models Wounds and Injuries Male Middle Aged Accidental Falls Adolescent Decision Trees Principal Component Analysis Aged Young Adult Adult Algorithms Retrospective Studies Female Artificial Intelligence Machine Learning Humans
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Real-Time Postural Disturbance Detection Through Sensor Fusion of EEG and Motion Data Using Machine Learning.

Sensors (Basel, Switzerland) Dec 5, 2024
Millions of people around the globe are impacted by falls annually, making it a significant public health concern. Falls are particularly challenging to detect in real time, as they often occur suddenly and with little warning, highlighting the need ...
Humans Adult Posture Male Signal Processing, Computer-Assisted Postural Balance Accidental Falls Electroencephalography Machine Learning Algorithms Female
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Exploiting the features of deep residual network with SVM classifier for human posture recognition.

PloS one Dec 5, 2024
Over the last decade, there have been a lot of advances in the area of human posture recognition. Among multiple approaches proposed to solve this problem, those based on deep learning have shown promising results. Taking another step in this directi...
Humans Deep Learning Posture Neural Networks, Computer Accidental Falls Algorithms Support Vector Machine
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Effects of Robot-Assisted Gait Training on Balance and Fear of Falling in Patients With Stroke: A Randomized Controlled Clinical Trial.

American journal of physical medicine & rehabilitation Dec 3, 2024
OBJECTIVE: The aim of this study was compare the effects of combined training, which included robot-assisted gait training in addition to traditional balance training, and traditional balance training alone on balance and fear of falling in patients ...
Accidental Falls Treatment Outcome Robotics Aged Male Humans Middle Aged Female Exercise Therapy Postural Balance Fear Stroke Stroke Rehabilitation Gait Gait Disorders, Neurologic
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A Machine Learning-Based Prediction Model for the Probability of Fall Risk Among Chinese Community-Dwelling Older Adults.

Computers, informatics, nursing : CIN Dec 1, 2024
Fall is a common adverse event among older adults. This study aimed to identify essential fall factors and develop a machine learning-based prediction model to predict the fall risk category among community-dwelling older adults, leading to earlier i...
Machine Learning Female Risk Factors Aged Humans East Asian People Bayes Theorem Probability Independent Living China Accidental Falls Logistic Models Aged, 80 and over Male Risk Assessment
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Relationship of Community Mobility, Vital Space, and Faller Status in Older Adults.

Sensors (Basel, Switzerland) Nov 29, 2024
UNLABELLED: Community mobility, encompassing both active (e.g., walking) and passive (e.g., driving) transport, plays a crucial role in maintaining autonomy and social interaction among older adults. This study aimed to quantify community mobility in...
Aged Walking Humans Aged, 80 and over Geographic Information Systems Accelerometry Female Accidental Falls Male Independent Living Support Vector Machine
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Dynamic Tracking and Real-Time Fall Detection Based on Intelligent Image Analysis with Convolutional Neural Network.

Sensors (Basel, Switzerland) Nov 22, 2024
As many countries face rapid population aging, the supply of manpower for caregiving falls far short of the increasing demand for care. Therefore, if the care system can continuously recognize and track the care recipient and, at the first sign of a ...
Accidental Falls Image Processing, Computer-Assisted Humans Neural Networks, Computer Algorithms
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Reduction of Vision-Based Models for Fall Detection.

Sensors (Basel, Switzerland) Nov 13, 2024
Due to the limitations that falls have on humans, early detection of these becomes essential to avoid further damage. In many applications, various technologies are used to acquire accurate information from individuals such as wearable sensors, envir...
Neural Networks, Computer Algorithms Accidental Falls Wearable Electronic Devices Image Processing, Computer-Assisted Humans
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AI-assisted assessment of fall risk in multiple sclerosis: A systematic literature review.

Multiple sclerosis and related disorders Oct 16, 2024
BACKGROUND: Multiple sclerosis (MS) is an autoimmune disease that can increase the risk of falls in patients due to various factors. Traditional clinical assessments may not effectively identify those at risk of falling.
Artificial Intelligence Machine Learning Risk Assessment Humans Accidental Falls Multiple Sclerosis
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Deep feature fusion with computer vision driven fall detection approach for enhanced assisted living safety.

Scientific reports Sep 15, 2024
Assisted living facilities cater to the demands of the elderly population, providing assistance and support with day-to-day activities. Fall detection is fundamental to ensuring their well-being and safety. Falls are frequent among older persons and ...
Assisted Living Facilities Humans Aged Algorithms Deep Learning Accidental Falls
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