Assessment of Joint Angle and Reach Envelope Demands Using a Video-Based Physical Demands Description Tool

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.

Cubic B-spline Least-square Method Combine with a Quadratic Weight Function for Solving Integro-Differential Equations

In this article, a numerical scheme was implemented for solving the integro-differential equations (IDEs) with the weakly singular kernel by using a new scheme depend on the cubic B-spline least-square method and a quadratic B-spline as a weight function. The numerical results are in suitable agreement with the exact solutions via calculating L2 and L∞ norms errors. Theoretically, we discussed the stability evaluation of the current method using the Von-Neumann method, which explained that this technique is unconditionally stable.

A discounted least squares quadratic growth prediction model for use in 2 year toxicity studies

Weekly weighings of the laboratory rats are required to determine the correct dosage for mixing in the food. This creates problems in that the food mixing must be done immediately after the weighings and staff are often heavily taxed to perform the task. A discounted least squares growth prediction model allows for prediction of weights a week ahead of time, obviating the necessity for instantaneously processing the weight data. When dosages were prepared based on these predictions, for 10 treatment combinations 100% of the doses proved to be within 8·0% of the required dosage; 98·4% were within 5% of the required dosage; 78·7% were within 2% of the required dosage; and 51·6% were within 1% of the required dosage. The quadratic weight prediction model can also be incorporated into a model for predicting food consumption.