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Efficient one-day sampling of mechanical job exposure data - A study based on upper trapezius activity in cleaners and office workers

Författare

  • Svend Erik Mathiassen
  • A Burdorf
  • AJ van der Beek
  • Gert-Åke Hansson

Summary, in English

This ergonomics exposure assessment study compared the efficiency of eight 1-day-only strategies, that is, the relationship between the number of data collected per subject and the precision of the resulting mean exposure estimate. Whole-day electromyographic recordings from the right upper trapezius muscle in 24 cleaners and 23 office workers were processed to give minute-by-minute values of gap time and jerk time-parameters representing the level and frequency dimensions of muscle activation, respectively On-site observations provided data on time spent in each of eight exhaustive task categories in the job, seven of which were associated with activities during work, and the last comprising breaks. On average, sampling at fixed intervals without regard to tasks doubled efficiency as compared with random sampling, which in turn was several times as efficient as consecutive sampling. Stratified sampling according to the two broad categories, work and breaks, increased efficiency for random and fixed-interval sampling, but the gain was distinct only among cleaners (about 20%). The commonly used strategy in ergonomic studies of sampling consecutively for short periods within tasks was highly inefficient. Further classification of work into the seven subcategories resulted in marginal additional increases in efficiency; on average less than 2%. A decision algorithm is given for determining appropriate sampling strategies in different types of jobs.

Publiceringsår

2003

Språk

Engelska

Sidor

196-211

Publikation/Tidskrift/Serie

American Industrial Hygiene Association Journal

Volym

64

Issue

2

Dokumenttyp

Artikel i tidskrift

Förlag

Taylor & Francis

Ämne

  • Environmental Health and Occupational Health

Nyckelord

  • precision
  • mechanical exposure
  • ergonomics
  • efficiency
  • data collection
  • task analysis

Status

Published

ISBN/ISSN/Övrigt

  • ISSN: 1542-8117