臺灣博碩士論文加值系統

摘要 i
Abstract iii
誌謝 v
發表清冊 vi
Table of Contents ix
List of Tables xiii
List of Figures xiv
Chapter 1 Introduction 1
1.1 Motivation and Objectives 1
1.2 Contributions 2
1.3 Dissertation Outline 5
Chapter 2 Care Needs of People with Illnesses 6
2.1 Care Needs of People with Illnesses in Rehabilitation Phase 6
2.1.1 Care Needs of Elderly People 6
2.1.1.1 Physiological Condition Control 7
2.1.1.2 Fall Prevention 8
2.1.2 Care Needs of Patient with Schizophrenia 10
2.1.2.1 Physiological Condition Control 12
2.1.2.2 Symptoms and Psychological Condition Control 13
Chapter 3 Applications of Technology in Healthcare 19
3.1 Application of Kinect Depth Sensors 20
3.1.1 Gait and Balance 22
3.1.1.1 Introduction to Gait and Balance Assessment 23
3.1.1.2 Related Work of Gait and Balance Assessment by Using Kinect 24
3.1.2 Motion Identification 25
3.1.2.1 Introduction to Extremity Identification 25
3.1.2.2 Related Work of Extremity Action Identification 26
3.1.2.3 Vision-Based Action Identification Techniques 27
3.1.3 Physical Rehabilitation by Using Kinect 29
Chapter 4 Application of Physical Evaluation and Rehabilitation by Using Kinect 33
4.1 Developing Postural Stability Features to Assess Body Joint Coordination Patterns 34
4.1.1 The Importance of Developing Postural Stability Features 34
4.1.2 Materials 35
4.1.2.1 Kinect Depth Sensor System 35
4.1.2.2 Participants 36
4.1.2.3 Standing Still Experiment 37
4.1.2.4 Data Processing 37
4.1.3 Methodology 38
4.1.3.1 Local Inter-Joint Coordination Pattern (IJCP) Feature 38
4.1.3.2 Global Inter-Joint Coordination Features 40
4.1.4 Results of Postural Stability Features of Body Joint Coordination Patterns 41
4.1.5 Discussion of Postural Stability Features of Body Joint Coordination Patterns 46
4.1.6 Conclusions of Postural Stability Features of Body Joint Coordination Patterns 49
4.2 An Upper Extremity Rehabilitation System Using Efficient Vision-Based Action Identification Techniques 50
4.2.1 The Proposed and the Proposed Action Identification System for Upper Extremity Rehabilitation at Home 50
4.2.2 Materials 52
4.2.2.1 Experimental Environment 52
4.2.3 The Proposed Methods 53
4.2.3.1 Depth / RGB Image Sensor 53
4.2.3.2 Skeletonizing 54
4.2.3.3 Skin Detection 58
4.2.3.4 Skeleton Point Establishment 59
4.2.3.5 Action Classifier 63
4.2.4 Results of Proposed Action Identification System 66
4.2.5 Discussion of Proposed System Comparison with Others 73
4.2.6 Conclusions of the Upper Extremity Rehabilitation System Using Efficient Vision-Based Action Identification Techniques 74
4.3 Effects of Rehabilitation Homecare System on Physical Fitness Promotion in Patients with Schizophrenia 76
4.3.1 Clinical Applications of Rehabilitation Homecare System on Physical Fitness Promotion in Patients with Schizophrenia 76
4.3.2 Materials and Methods of this Clinical Applications Experiment 76
4.3.2.1 Experimental Procedure 76
4.3.2.2 Participants 77
4.3.2.3 Experimental Materials 78
4.3.2.4 Measures of Physical Function 79
 6-Minute Walk Test (6MWT) 79
 Timed Up and Go Test (TUG) 79
4.3.2.5 Data Analyses 80
4.3.3 Results of Clinical Applications Experiment 80
4.3.4 Discussion of Effects of Rehabilitation Homecare System on Physical Fitness Promotion in Patients with Schizophrenia 87
4.3.5 Conclusions of Effects of Rehabilitation Homecare System on Physical Fitness Promotion in Patients with Schizophrenia 88
Chapter 5 Summary and Future Work 90
5.1 Conclusion 90
5.2 Future Work 92
References 94

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