Skip to main content
padlock icon - secure page this page is secure

Use of NIOSH equation inputs to calculate lumbosacral compression forces

Buy Article:

$61.00 + tax (Refund Policy)

The purpose of the current paper was to develop regression-based models that use NIOSH lifting equation H and V values to accurately calculate L /S compression 5 1 forces during symmetrical load-bearing tasks. Results from a linked-segment, biomechanical model were used as the criterion. Twenty-two subjects (11 males, 11 females) performed movements through a wide range of postures in the sagittal plane. Each model was developed with the data from 16 subjects ( n = 1704 postures) and validated with 6 subjects ( n = 750 postures). Five loads were iterated from 0 to 28 kg (females) or 36 kg (males) or until the strength demand at one joint exceeded the 98th percentile value predicted for that gender. Both models required the input of the NIOSH H and V values, subject body mass, load mass and trunk angle. MODEL1 used regression equations to calculate the moment arm from the load, and the upper body centre of mass, to the L /S joint. 5 1 These lengths were subsequently used in a biomechanical model to calculate the . joint compression force ( R 2 = 0 989, RMS error = 147 N). MODEL2 predicted compression force directly with one equation using the same inputs as MODEL1 . ( R 2 = 0 983, RMS error = 183 N, both models n = 6467). The results were slightly improved for both models when applied to the validation subject data ( n = 2303). Regression models were also developed to estimate the maximum and minimum expected trunk angles for all possible H and V combinations so that 'worst case' scenarios could be evaluated for given load positions.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics


Document Type: Research Article

Publication date: July 1, 1997

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more