Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Smart work clothes give better health - Through improved work technique, work organization and production technology
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Ergonomics.ORCID iD: 0000-0001-5338-0586
2019 (English)In: 20th Congress of the International Ergonomics Association, IEA 2018, Springer, 2019, Vol. 820, p. 515-519Conference paper, Published paper (Refereed)
Abstract [en]

Musculoskeletal disorders (MSDs) constitute a major health problem for employees, and the economic consequences are substantial for the individuals, companies and the society. The ageing population creates a need for jobs to be sustainable so that employees can stay healthy and work longer. Prevention of MSD risks therefore needs to become more efficient, and more effective tools are thus needed for risk management. The use of smart work clothes is a way to automate data collection instead of manual observation. The aim of this paper is to describe a new smart work clothes system that is under development, and to discuss future opportunities using new and smart technology for prevention of work injuries. The system consists of a garment with textile sensors woven into the fabric for sensing heart rate and breathing. Tight and elastic first layer work wear is the basis for these sensors, and there are also pockets for inertial measurement units in order to measure movements and postures. The measurement data are sent wireless to a tablet or a mobile telephone for analysis. Several employees can be followed for a representative time period in order to assess a particular job and its workplace. Secondly, the system may be used for individuals to practice their work technique. The system also gives relevant information to a coach who can give feedback to the employees of how to improve their work technique. Thirdly, the data analysis may also give information to production engineers and managers regarding the risks. The information will support decisions on the type of actions needed, the body parts that are critical and the emergency of taking action.

Place, publisher, year, edition, pages
Springer, 2019. Vol. 820, p. 515-519
Series
Advances in Intelligent Systems and Computing, ISSN 2194-5357 ; 820
Keywords [en]
Observation methods, Prevention, Wearables
National Category
Other Engineering and Technologies not elsewhere specified
Identifiers
URN: urn:nbn:se:kth:diva-233649DOI: 10.1007/978-3-319-96083-8_67Scopus ID: 2-s2.0-85051786651ISBN: 9783319960821 (print)OAI: oai:DiVA.org:kth-233649DiVA, id: diva2:1242576
Conference
20th Congress of the International Ergonomics Association, IEA 2018, Florence, Italy, 26 August 2018 through 30 August 2018
Note

QC 20180828

Available from: 2018-08-28 Created: 2018-08-28 Last updated: 2018-08-28Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Eklund, Jörgen

Search in DiVA

By author/editor
Eklund, Jörgen
By organisation
Ergonomics
Other Engineering and Technologies not elsewhere specified

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 3683 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf