Prediction of Ground Reaction Forces and Center of Pressure During Different Lifting Tasks Using Inverse Dynamics and Machine Learning Methods, M.Sc. Thesis Sharif University of Technology ; Arjmand, Navid (Supervisor)
Abstract
Ground reaction forces (GRFs) and their centers of pressure (CoPs) are essential inputs in musculoskeletal models of the spine that study load-lifting tasks. While GRFs and CoPs are usually measured in vivo via force-plates, they can be predicted based on motion equations, developed in AnyBody Modelling System (AMS) thus eliminating the need for laboratory equipment and in vivo measurements. This study aims to develop an easy-to-use yet accurate model that predict GRFs and CoPs during different Manual Material Handling (MMH) activities using AnyBody Modelling System and artificial neural networks. First, the accuracy of the AMS GRF prediction algorithm was evaluated for 8 normal- and 4...
Cataloging briefPrediction of Ground Reaction Forces and Center of Pressure During Different Lifting Tasks Using Inverse Dynamics and Machine Learning Methods, M.Sc. Thesis Sharif University of Technology ; Arjmand, Navid (Supervisor)
Abstract
Ground reaction forces (GRFs) and their centers of pressure (CoPs) are essential inputs in musculoskeletal models of the spine that study load-lifting tasks. While GRFs and CoPs are usually measured in vivo via force-plates, they can be predicted based on motion equations, developed in AnyBody Modelling System (AMS) thus eliminating the need for laboratory equipment and in vivo measurements. This study aims to develop an easy-to-use yet accurate model that predict GRFs and CoPs during different Manual Material Handling (MMH) activities using AnyBody Modelling System and artificial neural networks. First, the accuracy of the AMS GRF prediction algorithm was evaluated for 8 normal- and 4...
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