A polynomial equation to predict low back compression force: accounting for the effects of load height on instability.
The purpose of this study was to develop a regression equation that, incorporating the potential energy of the load in the hands, was capable of improved predictions of spinal compression forces. A stepwise polynomial equation was developed from EMG profiles of 15 muscles, and its spinal joint loading predictions at L4/L5 were compared to current methods of calculating spinal compression. Absolute muscle activation was shown to increase with increased loading height, indicating that the central nervous system responds to changes in spinal stability. The inclusion of potential energy into the calculation of spinal disc compression at L4/L5 improved estimates of the compressive forces acting on the spine. This is the first model to incorporate potential energy into a predictive model for lumbar spine compression without the use of electromyography. It was concluded that potential energy plays a vital role in dictating the recruitment patterns of the trunk.
Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA. calder.inger@mayo.edu
Inger Christina
IC
Calder
Jim R
JR
Potvin
D000328:Adult; D000465:Algorithms; D002170:Canada; D004576:Electromyography; D005240:Feasibility Studies; D005260:Female; D005544:Forecasting; D006801:Humans; D017770:Lifting; D008161:Lumbosacral Region; D008297:Male; D012044:Regression Analysis; D013117:Spinal Cord Compression / Q000175:diagnosis*; D016474:Weight-Bearing / Q000502:physiology*; D055815:Young Adult