Human Whole-Body Static 3D Posture Prediction in One- and Two-Handed Lifting Tasks from Different Load Positions using Machine Learning, M.Sc. Thesis Sharif University of Technology ; Arjmand, Navid (Supervisor)
Abstract
Biomechanical models require body posture to evaluate the risk of musculoskeletal injuries during daily/occupational activities like manual material handling (MMH). The procedure to measure body posture via motion-analysis techniques is complex, time-consuming, and limited to equipped laboratories. This study aims to develop an easy-to-use yet accurate model that predict human whole-body static posture (3D body coordinates and anatomical joint angles) during different MMH activities. Twenty healthy male right-handed individuals with body mass index between 18 and 26 performed 204 symmetric and asymmetric MMH activities. Each person reached (i.e., without any load in hands) the destinations...
Cataloging briefHuman Whole-Body Static 3D Posture Prediction in One- and Two-Handed Lifting Tasks from Different Load Positions using Machine Learning, M.Sc. Thesis Sharif University of Technology ; Arjmand, Navid (Supervisor)
Abstract
Biomechanical models require body posture to evaluate the risk of musculoskeletal injuries during daily/occupational activities like manual material handling (MMH). The procedure to measure body posture via motion-analysis techniques is complex, time-consuming, and limited to equipped laboratories. This study aims to develop an easy-to-use yet accurate model that predict human whole-body static posture (3D body coordinates and anatomical joint angles) during different MMH activities. Twenty healthy male right-handed individuals with body mass index between 18 and 26 performed 204 symmetric and asymmetric MMH activities. Each person reached (i.e., without any load in hands) the destinations...
Find in contentBookmark |
|