Two posture analysis approaches and their application in a modified Rapid Upper Limb Assessment evaluation

Abstract

This paper presents two posture risk quantification methods: first, an event-based method where the most common and the worst postures are estimated in a task; second, a time-based method where posture distributions are calculated from random samples of observed postures in the task. A ‘click-on-screen’ posture data entry method was developed for the time-based posture analysis method to make the observation process easier and to reduce possible posture categorization bias. Both methods were used to quantify various work posture parameters among a study cohort of 733 subjects from a prospective epidemiological study of upper extremity musculoskeletal disorders. Composite posture indices using a modified Rapid Upper Limb Assessment (RULA) method were also computed using data obtained by the two posture analysis methods. Results showed that both methods were able to distinguish jobs with large differences in certain posture measures. However, they did not produce the same results and could not be used interchangeably. Risk evaluation criteria should be developed, either for specific posture parameters or as a composite index, with a well-defined postural analysis method, so that users can follow exact procedures and obtain comparable results. The event-based method is easy to use and may suit practitioners better, while the time-based method adds more information to the measurement and may suit users who want more detailed information about posture exposure.

Keywords:

• Task-based analysis
• Event-based analysis
• Work-related musculoskeletal disorders

Acknowledgement

We acknowledge the important contributions of Ruby Irving, Benjamin Hamilton, Cindy Orr, Jessica Keller, Larry Taing, Pat Woods, Tiffany Ballard, Hieu Pham, Christina Buntin and Nancy Caldwell in data collection and processing and of Caroline Smith in coordination of field data collections. This research was funded in part by the US National Institute for Occupational Safety and Health (OH1007316) and the Washington State Department of Labor and Industries.