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Tools for exposure assessment of physical risk factors


Biography

Overview
Assessment of duration and frequency of exposure of VDT workers to physical risk factors can be automated and be implemented on a large scale through computer software; however, conducting force and postural measurements in the field are costly. Therefore we will develop and validate a task-based exposure assessment tool that integrates individual duration and frequency of the exposure and that accounts for subject variability through measuring the subject's specific intensities of the force and postural exposures. Usage monitors can record the frequency and duration of computer work; however, they record input device activities only and do not directly measure non-input device activities such as viewing the monitor. Most interactions with the computer are bounded by input device use allowing for indirect measurements of non-input device activities by assuming that small input device idle times are periods of non-input device activities. Therefore we will complete a pilot field study to determine the size of these small idles and validate that a computer usage monitor accurately records the complete user interaction. To identify and determine optimal sampling strategies for subject-specific exposure intensities, we will measure forces applied to the mouse and keyboard and wrist posture continuously on the same set of subjects in three scenarios: 1) while completing standardized tasks at a simulated workstation, 2) while completing the same standardized tasks at their own workstation, and 3) while completing their day-to-day work tasks at their own workstation across three days. Combined with a larger scale epidemiology study, these tools will be a critical development in the determination of the dose-response relationship for computer associated musculoskeletal disorders. Technology transfers include potential software products for computer users to monitor their own work patterns.
R01OH003997
DENNERLEIN, JACK TIGH

Time
1999-09-30
2009-08-31
Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.