台灣衛生署統計台灣99年10大死因，心血管疾病中的心臟疾病和腦血管疾病更是佔居第二和第三名之高；面對高齡化社會，老年人口比例不斷上升，心血管疾病已經是台灣不可忽視之疾病。動脈瘤就是心血管疾病之一，動脈瘤可以區分為五種類型，其中腎動脈下腹主動脈瘤最為常見，佔所有主動脈瘤80% 左右。在主動脈瘤的外科治療方法中主要是傳統剖腹手術和主動脈內人工支架血管置放手術。
為了讓病患有更好的術後生活品質，在家自行測量生理參數已是一重要趨勢，但若能加入專業判斷的服務，相信更將具有疾病預防的效益，而可以提供遠距監測功能的遠距健康照護系統是其中一個很好的應用工具。
在本研究我們提出一個主動式微型的生命跡象與活動感測器及多種通訊頻道整合而成的非侵入性微型遠距照護系統，利用此系統讓腹主動脈瘤病人可在戶外活動，擁有更安全放心的術後生活，也可減少因為醫護人力或家庭成員無法協助照護而發生憾事；再者，在持續長期的生理監控下，如非必要不必再回診，更能省下可觀的交通來回時間與醫療成本。

Statistics from Taiwan's Department of Health show that, among the 10 leading causes of death in 2010, heart disease and cerebrovascular disease in cardiovascular disease came in second and third place. Confronted by an aging society, the elderly population is rising, and cardiovascular disease is an disease that can no longer be ignored. A kind of cardiovascular disease, the aneurysm can be classified into 5 types, of which renal artery abdominal aortic aneurysm is most common and accounts for approximately  80% of all aortic aneurysms. In the surgical treatment of aortic aneurysms, traditional laparotomy and artificial vascular stent placement surgery are widely accepted.
In order to let patients have a better post-surgery life, measuring physiological parameters at their own home is becoming an important trend. But if professional judgment of the service can be added, it would be of help to disease prevention. And offering a Telehealth system with remote monitoring capability is one of the good application tools.
In this study, we a non-invasive micro Telecare system that integrates proactive tiny signs of life and activity sensors and variety of communication channels. This system allows abdominal aortic aneurysm patients to go outdoors and have a safer and securer post-surgery life. This also can reduce regrets due to no timely assistance from healthcare manpower or family. Besides, under continued long-term physiological monitoring, non-essential follow-ups can be spared, which can save considerable travel time and healthcare costs.

Contents
Chapter 1  General Background Information and Motivation 1
1.1  Motivation 1
1.2  Research Purpose 5
Chapter 2  Literature Review 8
2.1  Decision Support System (DSS) 8
2.1.1 Classification of Decision Support System 8
2.1.2 Physician-Patient Relationship Models 9
2.1.3 Difficulties for patients in decision-making participation 10
2.1.4 Reflections of patients’ preference and anticipation on medical quality 11
2.1.5 Common methods to show patients favorability rating 12
2.1.6 The application of patient-based decision support system 14
2.2  Sensor 18
2.2.1 Components of a Sensor 18
2.3  Micro-Electromechanical Systems (MEMS) 19
2.4  Cardiovascular Circulatory System 21
2.5  Classification of Aortic Aneurysm 22
2.5.1 Aortic Aneurysm 22
2.5.2 The Treatments For an Aortic Aneurysm 24
2.6  Literatures of Overseas and Domestics Researches on Telecare 26
2.6.1 Telecare Service 26
2.6.2 Related research on Telecare at home and abroad 28
Chapter 3  Research Methods 32
3.1  Research Procedure 32
3.1.1 Research procedure 33
3.1.2 System installation procedure 35
3.2  Research Methods 36
3.2.1 Smart phone 40
3.2.2 Physiological data sensor 40
3.3  Information System of Host 43
3.4  Subjects of long-distance care 45
Chapter 4  Results 48
4.1  Distance Physical Sign Dashboard 49
4.2  Real-time Physical Monitoring Record 50
4.3  Physical Data Analysis 58
4.4  Evaluation and Tracing of Disease 61
Chapter 5  Conclusion                                        64
5.1  Conclusion 64
5.2  Discussion 66
Reference 68
Health File Specification 73

Contents of Figures
Fig.1.1 Output Value from 2006-2010 in Taiwanese Health Care Industry 4
Fig.1.2 Main Components of Remote Patient Monitoring 4
Fig.2.1 Components Of a Sensor 18
Fig.2.2 The fabrication of wireless medical device with SoC/SiP 20
Fig.2.3 The design structure of the sensor with system-level integration 21
Fig.2.4 Cardiovascular Circulation System 22
Fig.2.5 Traditional Open Abdomen Surgery 25
Fig.2.6 A stent-graft with a catheter on abdominal aorta 26
Fig.3.1 Flowchart of research methods 34
Fig.3.2 System installation process 35
Fig.3.3 System process 39
Fig.3.4 Smart phone process 43
Fig.3.5 System structure 45
Fig.3.5 Partial result of pre-surgery blood test 47
Fig.3.6 Evaluation on patient’s living habit and chronic disease 47
Fig.4.1 Mobile Interface on Physical Sign Investigation 49
Fig.4.2 Distance Physical Sign Investigation Dashboard 49
Fig.4.3 Physical Investigation Record 50
Fig.4.4 Background Voice Record 51
Fig.4.5 Real-time Heart Rate Investigation 51
Fig.4.6 Real-time Respiratory Rate 51
Fig.4.7 Real-time Body Temperature Investigation 52
Fig.4.8 Real-time Position Investigation 52
Fig.4.9 Real-time Action Status Investigation 52
Fig.4.10 The Analysis of OLAP 53
Fig.4.11 Unified Communication 54
Fig.4.12 Demonstrates part of implemented code on Google HANGOUT 54
Fig.4.13 Results Analysis of Heart Rate and Breathing Rate 58
Fig.4.14 Results Analysis of Heart rate/ Breathing Rate/ HRV 59
Fig.4.15 Results Analysis of Breathing Rate/ RR 59
Fig.4.16 Results Analysis of RR 60
Fig.4.17 Results Analysis of ECG 60
Fig.4.18 Original Data 62
Fig.4.19 Data Mining Model-Neural Network 62
Fig.4.20 Data Mining Model-Decision Tree 63
Fig.4.21 The Clustering Analysis Model 63
 
Contents of Tables
Table 1 Mobile phone-end software functions 37

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