This paper proposes and compares two approaches that can identify different gait types of patients with hip osteoarthritis (OA) quantitatively using machine learning techniques. One is a simple and intuitive method that does not need clustering steps, and the other is a more detailed classification method that subdivides the gait classification results of the first method. Force plate measurements of 22 patients with hip OA and 18 healthy subjects without surgical history were collected and analyzed using principal component analysis (PCA) and Gaussian Mixture Model (GMM) to identify different types of gait. The physical meanings of the identified gait types are explained using the latent features of gait obtained from PCA and muscle forces calculated using OpenSim. The approaches will not only be useful for understanding the gait patterns of patients with hip OA but also will be applicable in analyzing different types of gait other than those of patients with hip OA.
Table Of Contents
I Introduction 1 II Method 2 2.1 Subjects 2 2.2 Instrument 2 2.3 Experiment protocol 4 2.4 Measured variables 4 2.5 Institutional review board 4 2.6 Dimension reduction methods 5 2.7 Similarity of gait patterns 7 2.8 Clustering methods 8 2.9 Muscle force estimation 9 III Result 10 3.1 Gait type classification using similarity of principal components 10 3.2 Gait type classification using Gaussian Mixture Model 12 3.3 Muscle forces of the identified gait types 15 IV Discussion 46 4.1 Comparison of the identified gait types 46 4.1.1 Characteristics of the similarity-based groups 46 4.1.2 Characteristics of the component-based groups 49 4.1.3 Comparison of the similarity-based and component-based groups 50 4.2 Physical implications of the gait types 51 4.2.1 Muscle forces of the gait types in spatial aspect 51 4.2.2 Muscle forces of the gait types in temporal aspect 54 4.3 Comparison of gait type classification methods 55 V Conclusion 57 References 58
Research on Human-friendly motion control; Development of human assistance;rehabilitation system; Design of robotic system based on human musculoskeletal system; Analysis of human walking dynamics and its application to robotics; 친인간적인 운동제어 설계연구; 인간 보조;재활 시스템의 설계 및 개발연구; 인간 근골격계에 기초한 로봇기구 개발연구; 보행운동 분석과 모델 및 로봇기구에의 응용