AIMC Topic: Accidental Falls

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Characterizing fall risk factors in Belgian older adults through machine learning: a data-driven approach.

BMC public health Nov 29, 2022
BACKGROUND: Falls are a major problem associated with ageing. Yet, fall-risk classification models identifying older adults at risk are lacking. Current screening tools show limited predictive validity to differentiate between a low- and high-risk of...
Humans Machine Learning Accidental Falls Belgium Independent Living Risk Factors Aged
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Deep Learning-Based Near-Fall Detection Algorithm for Fall Risk Monitoring System Using a Single Inertial Measurement Unit.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Sep 1, 2022
Proactively detecting falls and preventing injuries are among the primary keys to a healthy life for the elderly. Near-fall remote monitoring in daily life could provide key information to prevent future falls and obtain quantitative rehabilitation s...
Humans Algorithms Accidental Falls Activities of Daily Living Aged Deep Learning Monitoring, Ambulatory
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Using Healthcare Resources Wisely: A Predictive Support System Regarding the Severity of Patient Falls.

Journal of healthcare engineering Aug 1, 2022
BACKGROUND: An injurious fall is one of the main indicators of care quality in healthcare facilities. Despite several fall screen tools being widely used to evaluate a patient's fall risk, they are frequently unable to reveal the severity level of pa...
Humans Machine Learning Delivery of Health Care Accidental Falls Risk Factors Bayes Theorem Infant
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Inertial Data-Based AI Approaches for ADL and Fall Recognition.

Sensors (Basel, Switzerland) May 26, 2022
The recognition of Activities of Daily Living (ADL) has been a widely debated topic, with applications in a vast range of fields. ADL recognition can be accomplished by processing data from wearable sensors, specially located at the lower trunk, whic...
Humans Neural Networks, Computer Accidental Falls Artificial Intelligence Activities of Daily Living Algorithms
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Split BiRNN for real-time activity recognition using radar and deep learning.

Scientific reports May 6, 2022
Radar systems can be used to perform human activity recognition in a privacy preserving manner. This can be achieved by using Deep Neural Networks, which are able to effectively process the complex radar data. Often these networks are large and do no...
Human Activities Radar Humans Neural Networks, Computer Deep Learning Accidental Falls
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KinectGaitNet: Kinect-Based Gait Recognition Using Deep Convolutional Neural Network.

Sensors (Basel, Switzerland) Mar 29, 2022
Over the past decade, gait recognition had gained a lot of attention in various research and industrial domains. These include remote surveillance, border control, medical rehabilitation, emotion detection from posture, fall detection, and sports tra...
Emotions Gait Recognition, Psychology Neural Networks, Computer Accidental Falls Humans
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Crash test-based assessment of injury risks for adults and children when colliding with personal mobility devices and service robots.

Scientific reports Mar 28, 2022
Autonomous mobility devices such as transport, cleaning, and delivery robots, hold a massive economic and social benefit. However, their deployment should not endanger bystanders, particularly vulnerable populations such as children and older adults ...
Child Robotics Aged Accidental Falls Craniocerebral Trauma Pedestrians Accidents, Traffic Humans
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Application of Fuzzy and Rough Logic to Posture Recognition in Fall Detection System.

Sensors (Basel, Switzerland) Feb 18, 2022
Considering that the population is aging rapidly, the demand for technology for aging-at-home, which can provide reliable, unobtrusive monitoring of human activity, is expected to expand. This research focuses on improving the solution of the posture...
Recognition, Psychology Humans Algorithms Fuzzy Logic Posture Accidental Falls
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Finite Element Assessment of Bone Fragility from Clinical Images.

Current osteoporosis reports Dec 21, 2021
PURPOSE OF REVIEW: We re-evaluated clinical applications of image-to-FE models to understand if clinical advantages are already evident, which proposals are promising, and which questions are still open.
Fractures, Spontaneous Femoral Fractures Predictive Value of Tests Spinal Fractures Artificial Intelligence Reproducibility of Results Finite Element Analysis Risk Factors Osteoporotic Fractures Humans Accidental Falls
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LightAnomalyNet: A Lightweight Framework for Efficient Abnormal Behavior Detection.

Sensors (Basel, Switzerland) Dec 20, 2021
The continuous development of intelligent video surveillance systems has increased the demand for enhanced vision-based methods of automated detection of anomalies within various behaviors found in video scenes. Several methods have appeared in the l...
Humans Accidental Falls Neural Networks, Computer
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