Prediction of Peak Back Compressive Forces as a Function of Lifting Speed and Compressive Forces at Lift Origin and Destination - A Pilot Study

• Main Authors: Kasey O. Greenland (Author), Andrew S. Merryweather (Author), Donald S. Bloswick (Author)
• Format: Book
• Published: Elsevier, 2011-09-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 2093-7911; 10.5491/SHAW.2011.2.3.236
• Keywords: Lifting; Biomechanics; Linear models; Workplace; Risk assessment; Public aspects of medicine; RA1-1270
• Source: Safety and Health at Work, Vol 2, Iss 3, Pp 236-242 (2011)

Objectives: To determine the feasibility of predicting static and dynamic peak back-compressive forces based on (1) static back compressive force values at the lift origin and destination and (2) lifting speed. Methods: Ten male subjects performed symmetric mid-sagittal floor-to-shoulder, floor-to-waist, and waist-to-shoulder lifts at three different speeds (slow, medium, and fast), and with two different loads (light and heavy). Two-dimensional kinematics and kinetics were captured. Linear regression analyses were used to develop prediction equations, the amount of predictability, and significance for static and dynamic peak back-compressive forces based on a static origin and destination average (SODA) back-compressive force. Results: Static and dynamic peak back-compressive forces were highly predicted by the SODA, with R2 values ranging from 0.830 to 0.947. Slopes were significantly different between slow and fast lifting speeds (p < 0.05) for the dynamic peak prediction equations. The slope of the regression line for static prediction was significantly greater than one with a significant positive intercept value. Conclusion: SODA under-predict both static and dynamic peak back-compressive force values. Peak values are highly predictable and could be readily determined using back-compressive force assessments at the origin and destination of a lifting task. This could be valuable for enhancing job design and analysis in the workplace and for large-scale studies where a full analysis of each lifting task is not feasible.