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Wearable Sensors for Reliable Fall Detection

2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, 2005
Unintentional falls are a common cause of severe injury in the elderly population. By introducing small, non-invasive sensor motes in conjunction with a wireless network, the Ivy Project aims to provide a path towards more independent living for the elderly. Using a small device worn on the waist and a network of fixed motes in the home environment, we
Jay, Chen   +4 more
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Fall detection sensor for fall protection airbag

Proceedings of the 41st SICE Annual Conference. SICE 2002., 2003
The fall detection sensor for fall protection airbag was investigated to evaluate the airbag system. There are several methods to detect the fall: contact to the ground and detection of free fall. The problems with both methods are discussed. Since the usability of the latter come into practical use, tests in the future standard of airbag are discussed.
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Detecting Near-Fall Events

2022
Alexi Michael, UBC 3MT Semi-Finalist, presents their research on identifying fall risk by studying near-fall events. With the use of a sensor attached to the body, Alexi will be measuring and comparing the vibrations created in the human body during the motions experienced during near fall simulations and real-life daily motions.
openaire   +1 more source

Detecting falls by analyzing angular momentum

2011 IEEE International Conference on Rehabilitation Robotics, 2011
The aim of the present pilot study is to investigate the hypothesis that fall detection systems based on sensors placed on the distal segments of the body are more effective than solution based on placing sensors on the trunk. To test this hypothesis, we observed the contribution of all body segments to the 3D angular momentum. Five healthy adults were
MARTELLI, Dario   +2 more
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A fall detection and near-fall data collection system

2008 1st Microsystems and Nanoelectronics Research Conference, 2008
The FANFARE project has developed a system to fulfill the need for a wearable device to collect data for fall analysis. The system consists of a computer and a wireless sensor network to measure, display and store fall related parameters such as postural activities and heart rate variability. Ease of use and low power were considered in the design. The
A. Dinh   +11 more
openaire   +1 more source

A Hybrid Algorithm for Fall Detection

2017
Falling is a major problem among the people globally, frequently due to some health problems including vision loss or balance disorder as a consequence of aging. As a result of the falling in elder people; injuries, complications, neurological problems and mortality are generally occurred.
Serkan, Turkeli   +4 more
openaire   +2 more sources

Fall-MobileGuard: a Smart Real-Time Fall Detection System

Proceedings of the 10th EAI International Conference on Body Area Networks, 2015
This paper proposes Fall-MobileGuard, a novel real-time non-invasive fall detection and alarm notification system. The proposed system, in particular, is able to recognize different types of falls and is based on a wearable inertial sensor node, equipped with a tri-axial accelerometer, worn at the waist and a personal mobile device.
FORTINO, Giancarlo, Gravina R.
openaire   +1 more source

Fall Detection Using Smartphone Audio Features

IEEE Journal of Biomedical and Health Informatics, 2016
An automated fall detection system based on smartphone audio features is developed. The spectrogram, mel frequency cepstral coefficents (MFCCs), linear predictive coding (LPC), and matching pursuit (MP) features of different fall and no-fall sound events are extracted from experimental data. Based on the extracted audio features, four different machine
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Fall & ADL Detection Methodologies for AAL

2015
The monitoring of falls and Activities of Daily Living (ADL) is a fundamental task to implement a rigorous remote monitoring of weak users with particular regards to elderlies. Actually, unintentional falls cause a lot of hospitalizations and could produce serious consequences due to long-lie happenings.
ANDO', Bruno   +4 more
openaire   +1 more source

Fall Detection

2022
Jakub Wagner   +2 more
openaire   +1 more source

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