A system for predicting and preventing work-related musculoskeletal disorders among dentists
Bhornsawan Thanathornwong , Siriwan Suebnukarn , Yupin Songpaisan & Kan Ouivirach (2012): A system for predicting and preventing work-related musculoskeletal disorders among dentists, Computer Methods in Biomechanics and Biomedical Engineering, DOI:10.1080/10255842.2012.672565
(Received 15 December 2011; final version received 1 March 2012)
Work-related musculoskeletal disorders (WMSDs) have become increasingly common among dentists and initiate a series
of events that could result in a career ending. This study aims to construct a system for predicting and preventing WMSD
among dentists. We used Bayesian network (BN) that describes the mutual relationships among multiple variables
contributing to WMSDs. The data-sets were prepared from direct measurements of dentist’s movements and a questionnaire
survey. We applied BN learning algorithms to the training data-sets to develop WMSD prediction model using 10-fold
cross-validation. To evaluate the system performance, 16 dentists were randomly assigned into a 2 £ 2 crossover trial
scheduled to each of two sequences of dental working: receiving feedback or no feedback including the probability of
WMSD and related risk factors from the system. The group that received feedback decreased significantly (t-test, p , 0.05)
the extensions of neck and upper back in the y-axis as well as the WMSD probability on the post-test. In conclusion, the
system for predicting and preventing WMSD aids the correction of neck and upper back extensions and reduction in WMSD
probability, which may potentially contribute to reduce the risk of WMSD among dentists.
Keywords: Bayesian network; work-related musculoskeletal disorders; dentist
