Literature DB >> 18403286

Portable preimpact fall detector with inertial sensors.

Ge Wu1, Shuwan Xue.   

Abstract

Falls and the resulting hip fractures in the elderly are a major health and economic problem. The goal of this study was to investigate the feasibility of a portable preimpact fall detector in detecting impending falls before the body impacts on the ground. It was hypothesized that a single sensor with the appropriate kinematics measurements and detection algorithms, located near the body center of gravity, would be able to distinguish an in-progress and unrecoverable fall from nonfalling activities. The apparatus was tested in an array of daily nonfall activities of young (n=10) and elderly (n=14) subjects, and simulated fall activities of young subjects. A threshold detection method was used with the magnitude of inertial frame vertical velocity as the main variable to separate the nonfall and fall activities. The algorithm was able to detect all fall events at least 70 ms before the impact. With the threshold adapted to each individual subject, all falls were detected successfully, and no false alarms occurred. This portable preimpact fall detection apparatus will lead to the development of a new generation inflatable hip pad for preventing fall-related hip fractures.

Entities:  

Mesh:

Year:  2008        PMID: 18403286     DOI: 10.1109/TNSRE.2007.916282

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  28 in total

Review 1.  Fall detection with body-worn sensors : a systematic review.

Authors:  L Schwickert; C Becker; U Lindemann; C Maréchal; A Bourke; L Chiari; J L Helbostad; W Zijlstra; K Aminian; C Todd; S Bandinelli; J Klenk
Journal:  Z Gerontol Geriatr       Date:  2013-12       Impact factor: 1.281

2.  An environmental-adaptive fall detection system on mobile device.

Authors:  Sung-Yen Chang; Chin-Feng Lai; Han-Chieh Josh Chao; Jong Hyuk Park; Yueh-Min Huang
Journal:  J Med Syst       Date:  2011-03-22       Impact factor: 4.460

3.  An analysis of the accuracy of wearable sensors for classifying the causes of falls in humans.

Authors:  Omar Aziz; Stephen N Robinovitch
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2011-08-22       Impact factor: 3.802

Review 4.  The Elderly's Independent Living in Smart Homes: A Characterization of Activities and Sensing Infrastructure Survey to Facilitate Services Development.

Authors:  Qin Ni; Ana Belén García Hernando; Iván Pau de la Cruz
Journal:  Sensors (Basel)       Date:  2015-05-14       Impact factor: 3.576

5.  Estimation of Attitude and External Acceleration Using Inertial Sensor Measurement During Various Dynamic Conditions.

Authors:  Jung Keun Lee; Edward J Park; Stephen N Robinovitch
Journal:  IEEE Trans Instrum Meas       Date:  2012-01-08       Impact factor: 4.016

Review 6.  Fall detection devices and their use with older adults: a systematic review.

Authors:  Shomir Chaudhuri; Hilaire Thompson; George Demiris
Journal:  J Geriatr Phys Ther       Date:  2014 Oct-Dec       Impact factor: 3.381

7.  Development and evaluation of a prior-to-impact fall event detection algorithm.

Authors:  Jian Liu; Thurmon E Lockhart
Journal:  IEEE Trans Biomed Eng       Date:  2014-04-04       Impact factor: 4.538

8.  Statistical prediction of load carriage mode and magnitude from inertial sensor derived gait kinematics.

Authors:  Sol Lim; Clive D'Souza
Journal:  Appl Ergon       Date:  2018-11-29       Impact factor: 3.661

9.  A Survey on Ambient Intelligence in Health Care.

Authors:  Giovanni Acampora; Diane J Cook; Parisa Rashidi; Athanasios V Vasilakos
Journal:  Proc IEEE Inst Electr Electron Eng       Date:  2013-12-01       Impact factor: 10.961

10.  Hip protectors: recommendations for biomechanical testing--an international consensus statement (part I).

Authors:  S N Robinovitch; S L Evans; J Minns; A C Laing; P Kannus; P A Cripton; S Derler; S J Birge; D Plant; I D Cameron; D P Kiel; J Howland; K Khan; J B Lauritzen
Journal:  Osteoporos Int       Date:  2009-10-06       Impact factor: 4.507

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