Multiple linear regression to develop strength scaled equations for knee and elbow joints based on age, gender and segment mass Online publication date: Fri, 26-Oct-2012
by Sonia D'Souza; John Rasmussen; Ansgar Schwirtz
International Journal of Human Factors Modelling and Simulation (IJHFMS), Vol. 3, No. 1, 2012
Abstract: The next 50 years will see a drastic increase in the older population. Digital human modelling is a valuable ergonomic tool to design safe and comfortable environments for the elderly. For this purpose, anthropometric dimensions, elbow peak torque (EPT) and knee peak torque (KPT) from a sample of 141 males and 142 females aged 50 to 80 years in Munich, Germany were collected. Males were significantly stronger than females across all age groups. For both genders, EPT was better preserved from 60s to 70s whereas KPT reduced significantly (P < 0.05) across all age groups. Strength scaled equations based on age, gender; upper/lower limb lengths and masses using multiple linear regressions were created and simplified by removing statistical redundancies. Gender, thigh mass and age best predicted KPT (R² = 0.60). Gender, forearm mass and age best predicted EPT (R² = 0.75). Good cross validation was established for both elbow and knee models.
Online publication date: Fri, 26-Oct-2012
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