Literature DB >> 25683554

Are pressure measurements effective in the assessment of office chair comfort/discomfort? A review.

Roland Zemp1, William R Taylor2, Silvio Lorenzetti2.   

Abstract

Nowadays, the majority of jobs in the western world involves sitting in an office chair. As a result, a comfortable and supported sitting position is essential for employees. In the literature, various objective methods (e.g. pressure measurements, measurements of posture, EMG etc.) have been used to assess sitting comfort/discomfort, but their validity remains unknown. This review therefore examines the relationship between subjective comfort/discomfort and pressure measurements while sitting in office chairs. The literature search resulted in eight papers that met all our requirements. Four studies identified a relationship between subjective comfort/discomfort and pressure distribution parameters (including correlations of up to r = 0.7 ± 0.13). However, the technique for evaluating subjective comfort/discomfort seems to play an important role on the results achieved, therefore placing their validity into question. The peak pressure on the seat pan, the pressure distribution on the backrest and the pressure pattern changes (seat pan and backrest) all appear to be reliable measures for quantifying comfort or discomfort.
Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Keywords:  Comfort; Office chair; Pressure measurements

Mesh:

Year:  2015        PMID: 25683554     DOI: 10.1016/j.apergo.2014.12.010

Source DB:  PubMed          Journal:  Appl Ergon        ISSN: 0003-6870            Impact factor:   3.661


  5 in total

1.  Towards a Holistic Model Explaining Hearing Protection Device Use among Workers.

Authors:  Olivier Doutres; Jonathan Terroir; Caroline Jolly; Chantal Gauvin; Laurence Martin; Alessia Negrini
Journal:  Int J Environ Res Public Health       Date:  2022-05-04       Impact factor: 4.614

2.  A Single Subject, Feasibility Study of Using a Non-Contact Measurement to "Visualize" Temperature at Body-Seat Interface.

Authors:  Zhuofu Liu; Vincenzo Cascioli; Peter W McCarthy
Journal:  Sensors (Basel)       Date:  2022-05-23       Impact factor: 3.847

3.  Application of Machine Learning Approaches for Classifying Sitting Posture Based on Force and Acceleration Sensors.

Authors:  Roland Zemp; Matteo Tanadini; Stefan Plüss; Karin Schnüriger; Navrag B Singh; William R Taylor; Silvio Lorenzetti
Journal:  Biomed Res Int       Date:  2016-10-27       Impact factor: 3.411

4.  Validation of an instrumented dummy to assess mechanical aspects of discomfort during load carriage.

Authors:  Patrick D Wettenschwiler; Simon Annaheim; Silvio Lorenzetti; Stephen J Ferguson; Rolf Stämpfli; Agnes Psikuta; René M Rossi
Journal:  PLoS One       Date:  2017-06-29       Impact factor: 3.240

5.  Mechanical Predictors of Discomfort during Load Carriage.

Authors:  Patrick D Wettenschwiler; Silvio Lorenzetti; Rolf Stämpfli; René M Rossi; Stephen J Ferguson; Simon Annaheim
Journal:  PLoS One       Date:  2015-11-03       Impact factor: 3.240

  5 in total

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