Simulation of Human Movements through Optimization

Optimization has been used to simulate human neural control and resulting movement patterns. The short term aim was to develop the methodology required for solving the movement optimization problem often arising when modelling human movements. A long term aim is the contribution to increased knowledge about various human movements, wherein postures is one specific case. Simulation tools can give valuable information to improve orthopeadic treatments and technique for training and performance in sports. In one study a static 3D model with 30 muscle groups was used to analyse postures. The activation levels of these muscles are minimized in order to represent the individual’s choice of posture. Subject specific data in terms of anthropometry, strength and orthopedic aids serve as input. The specific aim of this part was to study effects from orthopedic treatment and altered abilities of the subject. Initial validation shows qualitative agreement of posture strategies but further details about passive stiffness and anthropometry are needed, especially to predict pelvis orientation. Four studies dealt with movement optimization. The main methodological advance was to introduce contact constraints to the movement optimization. A freetime multiple phase formulation was derived to be able to analyse movements where different constraints and degrees of freedom are present in subsequent phases of the movements. The athletic long jump, a two foot high jump, a backward somersault and rowing were used as applications with their different need of formulation. Maximum performance as well as least effort cost functions have been explored. Even though it has been a secondary aim in this work the results show reasonable agreement to expected movements in reality. Case specific subject properties and inclusion of muscle dynamics are required to draw conclusions about improvements in the sport activity, respectively.QC 20120910