Affiliation:
1. McMaster University, Hamilton, Canada
2. MyAbilities Technologies Inc., Burlington, Canada
Abstract
Background Current methods for describing physical work demands often lack detail and format standardization, require technical training and expertise, and are time-consuming to complete. A video-based physical demands description (PDD) tool may improve time and accuracy concerns associated with current methods. Methods Ten simulated occupational tasks were synchronously recorded using a motion capture system and digital video. The tasks included a variety of industrial tasks from lifting to drilling to overhead upper extremity tasks of different cycle times. The digital video was processed with a novel video-based assessment tool to produce 3D joint trajectories (PDAi), and joint angle and reach envelope measures were calculated and compared between both data sources. Results Root mean squared error between video-based and motion capture posture estimated ranged from 89.0 mm to 118.6 mm for hand height and reach distance measures, and from 13.5° to 21.6° for trunk, shoulder, and elbow angle metrics. Continuous data were reduced to time-weighted bins, and video-based posture estimates showed 75% overall agreement and quadratic-weight Cohen’s kappa scores ranging from 0.29 to 1.0 compared to motion capture data across all posture metrics. Conclusion and Application The substantial level of agreement between time-weighted bins for video-based and motion capture measures suggest that video-based job task assessment may be a viable approach to improve accuracy and standardization of field physical demands descriptions and minimize error in joint posture and reach envelope estimates compared to traditional pen-and-paper methods.
Subject
Behavioral Neuroscience,Applied Psychology,Human Factors and Ergonomics
Cited by
5 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献