AIMC Topic: Accidental Falls

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Feature selection for elderly faller classification based on wearable sensors.

Journal of neuroengineering and rehabilitation May 30, 2017
BACKGROUND: Wearable sensors can be used to derive numerous gait pattern features for elderly fall risk and faller classification; however, an appropriate feature set is required to avoid high computational costs and the inclusion of irrelevant featu...
Humans Algorithms Retrospective Studies Accidental Falls Support Vector Machine Bayes Theorem Accelerometry Female Aged Adult Male
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A Combined One-Class SVM and Template-Matching Approach for User-Aided Human Fall Detection by Means of Floor Acoustic Features.

Computational intelligence and neuroscience May 30, 2017
The primary cause of injury-related death for the elders is represented by falls. The scientific community devoted them particular attention, since injuries can be limited by an early detection of the event. The solution proposed in this paper is bas...
Aged Accidental Falls Support Vector Machine Acoustics Normal Distribution Humans Algorithms
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Continuous detection of human fall using multimodal features from Kinect sensors in scalable environment.

Computer methods and programs in biomedicine May 25, 2017
BACKGROUND AND OBJECTIVES: Automatic detection of human fall is a key problem in video surveillance and home monitoring. Existing methods using unimodal data (RGB / depth / skeleton) may suffer from the drawbacks of inadequate lighting condition or u...
Environment Support Vector Machine Monitoring, Physiologic Motion Humans Biomechanical Phenomena Accidental Falls
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Artificial neural networks: Predicting head CT findings in elderly patients presenting with minor head injury after a fall.

The American journal of emergency medicine Nov 3, 2016
OBJECTIVES: To construct an artificial neural network (ANN) model that can predict the presence of acute CT findings with both high sensitivity and high specificity when applied to the population of patients≥age 65years who have incurred minor head i...
Humans Neural Networks, Computer Aged Male Accidental Falls Decision Support Systems, Clinical Forecasting Retrospective Studies Tomography, X-Ray Computed Female Trauma Centers Craniocerebral Trauma United States Regression Analysis Cost-Benefit Analysis
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Accelerometer and Camera-Based Strategy for Improved Human Fall Detection.

Journal of medical systems Oct 29, 2016
In this paper, we address the problem of detecting human falls using anomaly detection. Detection and classification of falls are based on accelerometric data and variations in human silhouette shape. First, we use the exponentially weighted moving a...
Pattern Recognition, Automated Accelerometry Support Vector Machine Bayes Theorem Monitoring, Ambulatory Humans Machine Learning Algorithms Accidental Falls
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Autoregressive-moving-average hidden Markov model for vision-based fall prediction-An application for walker robot.

Assistive technology : the official journal of RESNA Jul 22, 2016
Population aging of the societies requires providing the elderly with safe and dependable assistive technologies in daily life activities. Improving the fall detection algorithms can play a major role in achieving this goal. This article proposes a r...
Walking Markov Chains Monitoring, Ambulatory Walkers Algorithms Accidental Falls Regression Analysis Robotics Humans
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Sequence Learning with Passive RFID Sensors for Real-Time Bed-Egress Recognition in Older People.

IEEE journal of biomedical and health informatics Jun 2, 2016
Getting out of bed and ambulating without supervision is identified as one of the major causes of patient falls in hospitals and nursing homes. Therefore, increased supervision is proposed as a key strategy toward falls prevention. An emerging genera...
Female Aged Aged, 80 and over Beds Male Radio Frequency Identification Device Accidental Falls Support Vector Machine Humans Signal Processing, Computer-Assisted Machine Learning Monitoring, Ambulatory
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Social service robots to support independent living : Experiences from a field trial.

Zeitschrift fur Gerontologie und Geriatrie May 25, 2016
BACKGROUND: Assistive robots could be a future means to support independent living for seniors.
Needs Assessment Social Support Utilization Review Accidental Falls User-Computer Interface Robotics Humans Aged Female Aged, 80 and over Sweden Equipment Design Male Independent Living Man-Machine Systems Activities of Daily Living Patient Preference Austria Self-Help Devices Equipment Failure Analysis
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Designing a social and assistive robot for seniors.

Zeitschrift fur Gerontologie und Geriatrie May 25, 2016
BACKGROUND: The development of social assistive robots is an approach with the intention of preventing and detecting falls among seniors. There is a need for a relatively low-cost mobile robot with an arm and a gripper which is small enough to naviga...
Male Social Support Accidental Falls User-Computer Interface Robotics Equipment Design Activities of Daily Living Equipment Failure Analysis Female Sweden Aged Aged, 80 and over Needs Assessment Humans Man-Machine Systems Utilization Review Patient Preference Self-Help Devices
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A decision model to predict the risk of the first fall onset.

Experimental gerontology Apr 23, 2016
BACKGROUND: Miscellaneous features from various domains are accepted to be associated with the risk of falling in the elderly. However, only few studies have focused on establishing clinical tools to predict the risk of the first fall onset. A model ...
Risk Assessment Female Humans France Accidental Falls Risk Factors Machine Learning Follow-Up Studies Aged Prospective Studies Postural Balance Male
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