Literature DB >> 22256171

Optimum gravity vector and vertical acceleration estimation using a tri-axial accelerometer for falls and normal activities.

Alan K Bourke1, Karol O'Donovan, Amanda Clifford, Gearóid ÓLaighin, John Nelson.   

Abstract

UNLABELLED: This study aims to determine an optimum estimate for the gravitational vector and vertical acceleration profiles using a body-worn tri-axial accelerometer during falls and normal activities of daily living (ADL), validated using a camera based motion analysis system. Five young healthy subjects performed a number of simulated falls and normal ADL while trunk kinematics were measured by both an optical motion analysis system and a tri-axial accelerometer. Through low-pass filtering of the trunk tri-axial accelerometer signal between 1 Hz and 2.7 Hz using a 1(st) order or higher, Butterworth IIR filter, accurate gravity vector profile can be obtained using the method described here.
RESULTS: A high mean correlation (≥ 0.83: Coefficient of Multiple Correlations) and low mean percentage error (≤ 2.06 m/s(2)) were found between the vertical acceleration profile generated from the tri-axial accelerometer based sensor to those from the optical motion capture system. This proposed system enables optimum gravity vector and vertical acceleration profiles to be measured from the trunk during falls and normal ADL.

Mesh:

Year:  2011        PMID: 22256171     DOI: 10.1109/IEMBS.2011.6091947

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  5 in total

1.  Development and pilot study of a bed-exit alarm based on a body-worn accelerometer.

Authors:  K-H Wolf; K Hetzer; H M zu Schwabedissen; B Wiese; M Marschollek
Journal:  Z Gerontol Geriatr       Date:  2013-12       Impact factor: 1.281

Review 2.  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

3.  Development of a wearable-sensor-based fall detection system.

Authors:  Falin Wu; Hengyang Zhao; Yan Zhao; Haibo Zhong
Journal:  Int J Telemed Appl       Date:  2015-02-16

4.  Advanced analytical methods to assess physical activity behaviour using accelerometer raw time series data: a protocol for a scoping review.

Authors:  Tripti Rastogi; Anne Backes; Susanne Schmitz; Guy Fagherazzi; Vincent van Hees; Laurent Malisoux
Journal:  Syst Rev       Date:  2020-11-07

5.  Separating movement and gravity components in an acceleration signal and implications for the assessment of human daily physical activity.

Authors:  Vincent T van Hees; Lukas Gorzelniak; Emmanuel Carlos Dean León; Martin Eder; Marcelo Pias; Salman Taherian; Ulf Ekelund; Frida Renström; Paul W Franks; Alexander Horsch; Søren Brage
Journal:  PLoS One       Date:  2013-04-23       Impact factor: 3.240

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.