Improving Rehabilitation Practice Through the Analysis of Musculoskeletal Muscle and Joint Forces during Motion

Author: Arshdeep Singh Gill

Gill, Arshdeep Singh, 2017 Improving Rehabilitation Practice Through the Analysis of Musculoskeletal Muscle and Joint Forces during Motion, Flinders University, School of Computer Science, Engineering and Mathematics

This electronic version is made publicly available by Flinders University in accordance with its open access policy for student theses. Copyright in this thesis remains with the author. This thesis may incorporate third party material which has been used by the author pursuant to Fair Dealing exceptions. If you are the owner of any included third party copyright material and/or you believe that any material has been made available without permission of the copyright owner please contact copyright@flinders.edu.au with the details.

Abstract

Background: The child suffering from cerebral palsy shows abnormal gait. The condition of child who have abnormal gait will get worst if left untreated. The precise information about muscle and joint forces produced in children who have pathological gait is vital for describing the contribution of individual muscle in gait. This will help in developing new techniques to speed up their rehabilitation. Because the direct estimation of muscle forces in vivo is impractical. The joint kinematic and ground reaction force data from gait investigation trials are regularly utilized as part of musculoskeletal simulation to predict muscle forces. Aim: The purpose of this project is to obtain muscle forces in cerebral palsy patients and compare these with forces obtained from the same muscles in the case of normal subjects. Methods: An open source software known as opensim is used to estimate individual muscle forces by optimization technique. Three-dimensional computer model (included in opensim software) of the human musculoskeletal system is used to run simulations. The name of model used is gait2354. There are total 4 subjects with one trial each. One of them is normal and 3 have cerebral palsy. First of all, dynamic musculoskeletal model has its size readjusted to coordinate the subject’s size and shape. The use of kinematic equations is made to obtain the joint torque that best reproduce the marker trajectories got from motion capture system. In the end static optimization is used to obtain individual muscle forces joint torque at all-time intervals. Results: Graphs of Muscles forces at lower limbs during gait cycle is generated and comparison is done between normal gait and abnormal gait. Reasonably good correlation between calculated muscle forces and function of muscles is found. Muscle forces calculated in cerebral palsy patients were analysed by correlating them with gait abnormality seen in patient. Conclusion: This study successfully identified the muscles responsible for abnormal gait pattern. Higher muscle forces are observed in children having abnormal gait due to cerebral palsy and because of this hip and knee joint reaction forces are also high. Similar finding are given by previous researches. Justification of results coming out of simulation is also done by considering the anatomic game plan of muscle in respect to the skeletal structure in actual human body. Considering everything, it is revealed that model used in this project could be used to get general idea about the muscle responsible for abnormal gait pattern in cerebral palsy child. Future work: For further validation of results, the reliance on kinematics and ground reaction forces should have to be lessen by making use of forward dynamic optimisation which also enables to learn more, i.e. power, length, speed, actuation connections of the muscles, and with recorded electromyography signals during walking. Also, the generic parametrized model which comes with opensim requires modification for cerebral palsy subjects.

Keywords: Cerebral palsy, abnormal gait, muscle forces, joint forces, musculoskeletal modelling, musculoskeletal simulation,opensim
Subject: Engineering thesis

Thesis type: Masters
Completed: 2017
School: School of Computer Science, Engineering and Mathematics
Supervisor: Dr Saulo Martelli