Currently, there are no standards for the development of posture classification systems used in observation-based ergonomic posture assessment methods. This study was conducted to determine if an optimal posture category size for different body segments and posture views could be established by examining the trade-off between magnitude of error and the number of posture category misclassification errors made. Three groups (trunk flexion/extension and lateral bend; shoulder flexion/extension and adduction/abduction; elbow flexion/extension) of 30 participants each selected postures they perceived to correctly represent the video image shown on a computer screen. For each view, 10 images were presented for five different posture category sizes, three times each. The optimal posture category sizes established were 30 degrees for trunk, shoulder and elbow flexion/extension, 30 degrees for shoulder adduction/abduction and 15 degrees for trunk lateral bend, suggesting that posture category size should be based on the body segment and view of the image being assessed. Across all conditions, the posture category sizes were comparable to those used in published ergonomic tools.
The salience of posture diagrams used in observation-based posture assessment tools was evaluated with respect to analyst error rates and decision times. The best performance resulted from incorporating a grey border to the posture diagrams; a simple enhancement that can be made to most current observation-based posture assessment tools.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.