Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/29520
Title: Wearable technology for posture monitoring at the workplace
Authors: Bootsman, Rik
Markopoulos, Panos
Qi,Qi
Wang,Qi
TIMMERMANS, Annick 
Issue Date: 2019
Publisher: ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
Source: International Journal of Human Computer Studies, 132, p. 99-111
Abstract: Prolonged strenuous postures in occupational context may lead to low back pain. Avoiding such occurrences is known to help prevent low back pain episodes or may contribute to recovery. This research concerns wearable sensing technology to support posture monitoring for the prevention of occupational low back pain and, more specifically, how smart garments can help nurses avoid prolonged strenuous postures at work. We introduce BackUp, a system comprising of a smart shirt connected to a smartphone application that provides feedback and advice on low back posture, and we describe its design and implementation. We report on a series of studies that contributed to its development: an anthropometric study (N = 60) to decide on the placement of sensors on the lower spine; a brief field study aimed at evaluating user experience and attitudes towards the shirt (N = 17), and a second field study intended to assess its effectiveness in helping nurses avoid prolonged strenuous postures at work (N = 13). These studies demonstrate how smart clothing can support posture feedback in real life conditions. While the results from the field studies are encouraging regarding the potential of this technology, further research is needed to establish the durability of the behaviour modification achieved through smart garments.
Keywords: Smart garments; Interactive clothing; Posture correction; Low back pain;Persuasive technology; NurseUser test; Awareness
Document URI: http://hdl.handle.net/1942/29520
ISSN: 1071-5819
e-ISSN: 1095-9300
DOI: 10.1016/j.ijhcs.2019.08.003
ISI #: WOS:000491684200009
Rights: 2019 Elsevier Ltd. All rights reserved
Category: A1
Type: Journal Contribution
Validations: ecoom 2020
Appears in Collections:Research publications

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