Pulling force prediction using neural networks

International Journal of Occupational Safety and Ergonomics : JOSE
Rahul JainGovind Sharan Dangayach

Abstract

In ergonomics and human factors investigations, pulling force (PF) estimation has usually been achieved using various types of biomechanical models, and independent approximation of PF was done with the help of upper extremity joints. Recently, multiple regression methods have gained importance for task-relevant inputs in predicting PF. Artificial neural networks (ANNs) also play a vital role in fitting the data; however, their use in work-related biomechanics and ergonomics is inadequate. Therefore, the current research aimed to accomplish comparative investigation of ANN and regression models by assessing their capacity to predict PF values. Multipositional PF data were acquired from 200 subjects at three different handle heights and body locations. ANN and regression models were formed using a random sample of three subsets (75% training, 15% selection, 10% validation) for proving the outcomes. The comparison of ANN and regression models shows that the predictions of ANN models had a profoundly explained variance and lower root mean square difference values for the PF data at three handle heights. These outcomes advise that ANNs offer a precise and robust substitute for regression methods, and should be considered a useful m...Continue Reading

References

Jul 10, 1999·Journal of Biomechanics·J J FarawayD B Chaffin
Dec 22, 1999·International Journal of Occupational Safety and Ergonomics : JOSE·Robert A Kosiński, Cezary Kozłowski
Mar 15, 2003·International Journal of Occupational Safety and Ergonomics : JOSE·Tien-I LiuChongchan Lee
Sep 13, 2003·Journal of Biomedical Informatics·Stephan Dreiseitl, Lucila Ohno-Machado
Oct 28, 2003·International Journal of Occupational Safety and Ergonomics : JOSE·Leszek Morzyński, Grzegorz Makarewicz
Jan 5, 2013·Applied Ergonomics·Jia-Hua LinWayne Maynard
Feb 6, 2017·Archives of Environmental & Occupational Health·Rahul JainA K Bhardwaj

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Methods Mentioned

BETA
force measurement

Software Mentioned

Matlab
SPSS

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