Regression models for the prediction of dynamic L4/L5 compression forces during lifting

Abstract

The purpose of this study was to determine whether regression equations could be developed, as an alternative to biochemical models, to predict the peak L4(L5 disc compression force during dynamic, sagittal plane lifting. Eighteen male subjects performed a squat and a stoop lift with loads of 6, 14, 22, 29, and 32 kg. Each lift was analysed with a linked segment biomechanical model that output the compression force time history during the lift. The peak compression served as the dependent variable for two regression models. The independent variables in each model were measures which described the subject's body dimensions, body posture, internal lifting mechanics, load location and load effects. A ‘lab’ model was developed (R²=0·93) which required only four inputs and had an RMS error of only 8·3% between the biomechanical model estimate of the peak L4/L5 disc compression force and that predicted from the regression equation. A seven variable ‘field’ model was developed with an R² of 0·90 and an RMS error of 9·7%. It was concluded that both of the proposed models were potentially useful to the practising ergonomist interested in easily and quickly estimating lumbar compression forces during dynamic sagittal plane lifting.

Keywords:

• Dynamic lifting
• Biomechanical model
• Regression models
• Disc compression