Dissertation submitted in partial compliance with the requirements for the Masters Degree in Technology: Chiropractic, Durban University of Technology, 2010. / The aim of this study was to determine the inter-examiner reliability of motion palpation to detect joint dysfunction in hindfoot and midfoot joints of asymptomatic feet and feet with chronic ankle instability syndrome. The rationale for this study was that motion palpation is a commonly used assessment tool that is used by the chiropractic profession to detect the need for manipulation of the spine and extremities. Also until the reliability of motion palpation is known, other studies using motion palpation as an assessment tool to detect the need for manipulation in the hindfoot and midfoot are questionable. The study was conducted at Durban University of Technology (DUT). Patients that responded to the adverts were then screened via telephonic interview. The researcher performed a case history, physical examination and a foot and ankle regional examination on each patient. Three masters chiropractic students then independently assessed both the symptomatic and asymptomatic feet of each patient and recorded their results. The data was then statistically analysed using SPSS version 15. It was found that the inter-examiner reliability of motion palpation for detecting restrictions in feet with chronic ankle instability syndrome was fair and for detecting instability, there was moderate reliability. In the asymptomatic group the examiners showed to have poor reliability in detecting restrictions and moderate reliability in detecting instability. Inter-examiner reliability was better in the symptomatic group and in this group examiners had more agreement on detecting instability as opposed to restrictions. This study has showed that inter-examiner reliability ranged from poor to moderate in the symptomatic and asymptomatic group with the reliability ranging from poor to moderate. Therefore, one can conclude that motion palpation can be used as an assessment tool to detect joint dysfunction in hindfoot and midfoot joints. However, further studies are warranted to address other subjective and objective measurements such as tenderness and range of motion together with motion palpation.

Joint detection is vital for characterizing human pose and serves as a foundation for a wide range of computer vision applications such as physical training, health care, entertainment. This dissertation proposed two methods to detect joints in the human body for pose analysis. The first method detects joints by combining body model and automatic feature points detection together. The human body model maps the detected extreme points to the corresponding body parts of the model and detects the position of implicit joints. The dominant joints are detected after implicit joints and extreme points are located by a shortest path based methods. The main contribution of this work is a hybrid framework to detect joints on the human body to achieve robustness to different body shapes or proportions, pose variations and occlusions. Another contribution of this work is the idea of using geodesic features of the human body to build a model for guiding the human pose detection and estimation. The second proposed method detects joints by segmenting human body into parts first and then detect joints by making the detection algorithm focusing on each limb. The advantage of applying body part segmentation first is that the body segmentation method narrows down the searching area for each joint so that the joint detection method can provide more stable and accurate results.