Literature DB >> 21123104

Comparison of acceleration signals of simulated and real-world backward falls.

J Klenk1, C Becker, F Lieken, S Nicolai, W Maetzler, W Alt, W Zijlstra, J M Hausdorff, R C van Lummel, L Chiari, U Lindemann.   

Abstract

Most of the knowledge on falls of older persons has been obtained from oral reports that might be biased in many ways. Fall simulations are widely used to gain insight into circumstances of falls, but the results, at least concerning fall detection, are not convincing. Variation of acceleration and maximum jerk of 5 real-world backward falls of 4 older persons (mean age 68.8 years) were compared to the corresponding signals of simulated backward falls by 18 healthy students. Students were instructed to "fall to the back as if you were a frail old person" during experiment 1. In experiment 2, students were instructed not to fall, if possible, when released from a backward lean. Data acquisition was performed using a tri-axial acceleration sensor. In experiment 1, there was significantly more variation within the acceleration signals and maximum jerk was higher in the real-world falls, compared to the fall simulation. Conversely, all values of acceleration and jerk were higher for the fall simulations, compared to real-world falls in experiment 2. The present findings demonstrate differences between real-world falls and fall simulations. If fall simulations are used, their limitations should be noted and the protocol should be adapted to better match real-world falls.
Copyright © 2010 IPEM. Published by Elsevier Ltd. All rights reserved.

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Year:  2010        PMID: 21123104     DOI: 10.1016/j.medengphy.2010.11.003

Source DB:  PubMed          Journal:  Med Eng Phys        ISSN: 1350-4533            Impact factor:   2.242


  41 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

Review 2.  Proposal for a multiphase fall model based on real-world fall recordings with body-fixed sensors.

Authors:  C Becker; L Schwickert; S Mellone; F Bagalà; L Chiari; J L Helbostad; W Zijlstra; K Aminian; A Bourke; C Todd; S Bandinelli; N Kerse; J Klenk
Journal:  Z Gerontol Geriatr       Date:  2012-12       Impact factor: 1.281

3.  Smartphone-based solutions for fall detection and prevention: the FARSEEING approach.

Authors:  S Mellone; C Tacconi; L Schwickert; J Klenk; C Becker; L Chiari
Journal:  Z Gerontol Geriatr       Date:  2012-12       Impact factor: 1.281

Review 4.  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

5.  Real-World Accuracy and Use of a Wearable Fall Detection Device by Older Adults.

Authors:  Shomir Chaudhuri; Daan Oudejans; Hilaire J Thompson; George Demiris
Journal:  J Am Geriatr Soc       Date:  2015-11       Impact factor: 5.562

6.  Video capture of the circumstances of falls in elderly people residing in long-term care: an observational study.

Authors:  Stephen N Robinovitch; Fabio Feldman; Yijian Yang; Rebecca Schonnop; Pet Ming Leung; Thiago Sarraf; Joanie Sims-Gould; Marie Loughin
Journal:  Lancet       Date:  2012-10-17       Impact factor: 79.321

7.  Development of a standard fall data format for signals from body-worn sensors : the FARSEEING consensus.

Authors:  J Klenk; L Chiari; J L Helbostad; W Zijlstra; K Aminian; C Todd; S Bandinelli; N Kerse; L Schwickert; S Mellone; F Bagalá; K Delbaere; K Hauer; S J Redmond; S Robinovitch; O Aziz; M Schwenk; A Zecevic; T Zieschang; C Becker
Journal:  Z Gerontol Geriatr       Date:  2013-12       Impact factor: 1.281

8.  Evaluation of accelerometer-based fall detection algorithms on real-world falls.

Authors:  Fabio Bagalà; Clemens Becker; Angelo Cappello; Lorenzo Chiari; Kamiar Aminian; Jeffrey M Hausdorff; Wiebren Zijlstra; Jochen Klenk
Journal:  PLoS One       Date:  2012-05-16       Impact factor: 3.240

9.  Event-Centered Data Segmentation in Accelerometer-Based Fall Detection Algorithms.

Authors:  Goran Šeketa; Lovro Pavlaković; Dominik Džaja; Igor Lacković; Ratko Magjarević
Journal:  Sensors (Basel)       Date:  2021-06-24       Impact factor: 3.576

10.  Sit-stand and stand-sit transitions in older adults and patients with Parkinson's disease: event detection based on motion sensors versus force plates.

Authors:  Agnes Zijlstra; Martina Mancini; Ulrich Lindemann; Lorenzo Chiari; Wiebren Zijlstra
Journal:  J Neuroeng Rehabil       Date:  2012-10-07       Impact factor: 4.262

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