|Ph.D Student||Solav Dana|
|Subject||Non Rigid Kinematic Analysis in Various Biomechanical|
Applications Using Cosserat Point Theory
|Department||Department of Mechanical Engineering||Supervisors||Professor Alon Wolf|
|Professor Emeritus Miles Rubin|
|Full Thesis text|
Accurate quantitative motion analysis plays an essential role in understanding normal function as well as pathological conditions of human biomechanical systems. Optoelectronic stereophotogrammetry (OESP) is currently the state of the art in human motion analysis. This technique involves placing markers on the skin surface of the analyzed body segments and capturing their locations in space as a function of time. When the movement of the skeletal system is of interest, this noninvasive technique suffers from a critical limitation which is caused by the relative movement between the skin markers and the underlying bone. This limitation is often referred to as the soft tissue artifact (STA). STA is the most significant source of error in OESP, and a satisfactory solution for its compensation has not been devised yet, despite numerous efforts.
In this thesis, a novel method based on the theory of a Cosserat point is presented, to analyze the non-rigid kinematics of marker clusters, with an aim to reduce the STA and estimate more accurately the underlying bone pose. Specifically, a marker cluster on a body segment is divided into sub-clusters of three markers, each characterized by a triangular Cosserat point element (TCPE). The non-rigid kinematics of a TCPE was developed and the differences in the kinematics of the different TCPEs were characterized using scalar parameters of deformation. These parameters are evaluated in terms of their ability to identify subset groups of TCPEs which more accurately estimate the underlying bone pose.
The method was first evaluated using an experimental setup which consists of a rigid pendulum with a deformable implant attached to it, to simulate the soft tissue around a bony segment. Then, the method was further developed and tested using ex-vivo and in-vivo data of the lower limb. The results showed that the errors due to the STA can be reduced using the TCPE method, compared to commonly used least squares methods.
Moreover, the TCPE kinematic method was further developed for the purpose of respiratory motion analysis. In this study, chest wall (CW) kinematics measured using OESP was analyzed to evaluate respiratory function. The different breathing patterns of healthy subjects and neuromuscular patients were analyzed using the TCPE method, and results showed that they can be used to detect local asynchronies which are associated with respiratory inefficiency due to muscle weakness and dysfunction.