Video image-based posture assessment: an approach for dynamic working posture assessment

Abstract

Abstract Traditional observational posture evaluation methods stress on sampling approach for continuous evaluation of dynamic postures in any activity. Hence, the quality of results from such evaluations is under debate. This article proposes a Video Image-based Posture Assessment (VIPA) method as a highly capable one for assessing an activity requiring dynamic postures of workers. This article explains the various steps of VIPA and its application for (i) the extraction and classification of postures into different categories based on the instructed posture classes from 10 videos of soil loosening activity having 48,715 postures and (ii) the use of OWAS to evaluate the postures. VIPA relies on traditional posture evaluation methods. The results indicate that VIPA could identify precarious postures 30% of the activity duration; these results were found to be accurate and reliable because there is no sampling method involved. The capability of VIPA method is proven through the activity studied.