Literature DB >> 19665138

Optimal inertial sensor location for ambulatory measurement of trunk inclination.

Gert S Faber1, Idsart Kingma, Sjoerd M Bruijn, Jaap H van Dieën.   

Abstract

Trunk inclination (TI) is used often to quantify back loading in ergonomic workplace evaluation. The aim of the present study was to determine whether TI can be obtained using a single inertial sensor (IS) on the back, and to determine the optimal IS location on the back for the estimation of TI. Gold standard TI, the angle between the vertical and the line connecting the L5/S1 joint and the trunk centre of mass, was measured using an optoelectronic system. Ten subjects performed experimental trials, each consisting of a symmetric and an asymmetric lifting task, and of a left-right lateral flexion movement. Trials were repeated and, in between trials, the IS was shifted in small steps from a location on the thorax towards a location on the sacrum. Optimal IS location was defined as the IS location with minimum root-mean-square (RMS) error between the gold standard TI and the IS TI. Averaged over subjects, the optimal IS location for symmetric and asymmetric lifting was at about 25% of the distance from the midpoint between the posterior superior iliac spines (MPSIS) to the C7 spinous process. The RMS error at this location, averaged over subjects, was 4.6+/-2.9 degrees. For the left-right lateral flexion task, the optimal IS location was at about 30% of the MPSIS to C7 distance. Because in most activities of daily living, pure lateral flexion does not occur often, it is recommended place the IS at 25% of the distance from the MPSIS to C7.

Mesh:

Year:  2009        PMID: 19665138     DOI: 10.1016/j.jbiomech.2009.06.024

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  7 in total

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Authors:  Kevin Boldt; Anthony Killick; Walter Herzog
Journal:  J Appl Biomech       Date:  2015-08-06       Impact factor: 1.833

2.  Validation of Inertial Measurement Units for Upper Body Kinematics.

Authors:  Melissa M B Morrow; Bethany Lowndes; Emma Fortune; Kenton R Kaufman; M Susan Hallbeck
Journal:  J Appl Biomech       Date:  2017-06-26       Impact factor: 1.833

3.  Assessment of waveform similarity in clinical gait data: the linear fit method.

Authors:  M Iosa; A Cereatti; A Merlo; I Campanini; S Paolucci; A Cappozzo
Journal:  Biomed Res Int       Date:  2014-07-13       Impact factor: 3.411

4.  Evaluating physical function and activity in the elderly patient using wearable motion sensors.

Authors:  Bernd Grimm; Stijn Bolink
Journal:  EFORT Open Rev       Date:  2017-03-13

5.  Influence of different safety shoes on gait and plantar pressure: a standardized examination of workers in the automotive industry.

Authors:  Elke Ochsmann; Ulrike Noll; Rolf Ellegast; Ingo Hermanns; Thomas Kraus
Journal:  J Occup Health       Date:  2016-08-04       Impact factor: 2.708

6.  The role of wearables in spinal posture analysis: a systematic review.

Authors:  Lauren Simpson; Monish M Maharaj; Ralph J Mobbs
Journal:  BMC Musculoskelet Disord       Date:  2019-02-08       Impact factor: 2.362

7.  Trunk Flexion Monitoring among Warehouse Workers Using a Single Inertial Sensor and the Influence of Different Sampling Durations.

Authors:  Micaela Porta; Massimiliano Pau; Pier Francesco Orrù; Maury A Nussbaum
Journal:  Int J Environ Res Public Health       Date:  2020-09-28       Impact factor: 3.390

  7 in total

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