Universal Architecture Prototype for Patient-Centric Medical Environment

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研究生：	陳吳昀諺 Chen-Wu, Yun-Yen
論文名稱：	Universal Architecture Prototype for Patient-Centric Medical Environment 以病人為中心的醫療監控照護環境之架構與雛型
指導教授：	馬席彬 Ma, Hsi-Pin
口試委員:	汪重光 Wang, Chorng-Kuang 蔡佩芸 Tsai, Pei-Yun 黃柏鈞 Huang, Po-Chiun 何奕倫 Ho, Yi-Lwun
學位類別：	碩士 Master
系所名稱：	電機資訊學院 - 電機工程學系 Department of Electrical Engineering
論文出版年：	2011
畢業學年度：	100
語文別：	英文
論文頁數：	67
中文關鍵詞：	醫療環境、家庭照護系統、安卓作業系統、心電圖、腦電圖、室內定位
外文關鍵詞：	Medical Environment, Homecare System, Android, ECG, EEG, Indoor location determination
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Patient-centric medical environment is an important trend recently, which makes the medical organization provide healthcare information for patients. It also can save time for patients to go to hospital, improve patients life, and reduce the abuse cost for medical treatment.
In this thesis, a mobile healthcare system for patient-centric medical environment is proposed. The system provides the remote monitoring and emergency alarm in the patients’ own home. Also, the portability of system allows patients engage some outdoor activities. There are two main parts which discussed in this thesis. One is bio-signal capturing. Another is location services.
The sensor node, which is proposed in this thesis, captures electrocardiogram (ECG) and electroencephalogram (EEG) in the same time. The captured bio-signals will be shown on an Android phone or computer in realtime. Also, the physiological information can be synchronized to the medical server in hospital. On the other hand, a cardiac arrest detection is implemented by ECG analysis.
The second main part of this thesis is location service in patient-centric medical environment. The location service proposed by this thesis includes indoor location determination and outdoor location determination. The indoor location service determines the room-level location by detecting strength of existing WiFi signal. The accuracy in this thesis can reach to 76.2%. The outdoor location service determines location via the global location system
(GPS). These two main location services are implemented in the Android application.

近年來，以病人為中心的無線醫療環境日漸重要。它不只提供了病人的生理資訊，也為病患節省了到醫院做健康檢查所浪費的時間，進而延續病患的生命及節省醫院的醫療成本。

在這篇論文中，我們提出了一個適用於以病人為中心無線醫療環境的行動式健康監控系統。這個系統提供了在病患家中的遠端的健康監控與緊急狀況的警報機制。此外，由於系統的可攜性，病患即使進行戶外活動也可以即時的將健康狀態讓醫師可以掌握。本篇論文主要分為兩個部份討論，一為生理訊號的擷取，另一方面為定位服務。

本篇論文所提出的生理感測器可以同時擷取病患的心電圖和腦電圖。擷取到的生理訊號可以即時性的顯示在Android手機和電腦上。病患的生理資訊也可以藉由行動網路同步到位於醫院的醫療伺服器上。另一方面，藉由簡單的心電圖分析，心跳停止的監測也在此被實現了。

這篇論文的第二部份為以病人為中心的無線醫療環境中的定位服務。本篇論文所提出以病人為中心的無線醫療環境中的定位服務中包含了室內定位與室外定位。藉由室內現有WiFi訊號可以完成以房間為單位的定位。在本篇的室內定位精準度可以達到76.2%。而室外定位的部份是藉由全球定位系統來實現。本篇論文的室內室外定位皆實現於Android應用程式上。

Introduction 1
1 Backgrounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Introduction to Patient-Centric Medical Environment . . . . . . . . . 2
1.2 Introduction to Bio-Signals . . . . . . . . . . . . . . . . . . . . . . . 4
1.3 Review of Health Care System . . . . . . . . . . . . . . . . . . . . . 8
2 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
3 Organization of the Thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
System Description 11
1 Main Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2 General System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.1 Sensor and Front-End Circuit . . . . . . . . . . . . . . . . . . . . . 14
2.2 Micro-Processor and Analog to Digital Converter . . . . . . . . . . . 14
2.3 Short Range Wireless Transceiver . . . . . . . . . . . . . . . . . . . 15
2.4 Body Information Hub . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.5 Patient-Centric Medical Cloud . . . . . . . . . . . . . . . . . . . . . 16
Prototype Implementation (ECG monitoring and recording) 17
1 Related Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
1.1 Arduino . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
1.2 Bluetooth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
1.3 Bluetooth Protocol Stack . . . . . . . . . . . . . . . . . . . . . . . . 20
1.4 Android Application Development . . . . . . . . . . . . . . . . . . . 22
2 Prototype Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
3 Hardware Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.1 Design of Front-End Circuit . . . . . . . . . . . . . . . . . . . . . . 23
3.2 Implementation of ECG Front-End and Electrodes (3-Leads ECG Sen-
sor) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
3.3 Signal Sampling and Transmission . . . . . . . . . . . . . . . . . . . 27
3.4 Overview of Sensor Node Prototype . . . . . . . . . . . . . . . . . . 31
4 Software Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
4.1 Applications on Android Phone . . . . . . . . . . . . . . . . . . . . 31
4.2 Health Information Recording on PC . . . . . . . . . . . . . . . . . 37
4.3 Synchronization with Patient-Centric Medical Cloud . . . . . . . . . 37
5 Comparison . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
Multi-Sensor Expansion 41
1 System Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
2 EEG Front-End Circuit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
3 Sampling and Data Transmission in Multi-Sensor Expansion . . . . . . . . . 44
3.1 Two Sensors as an Example . . . . . . . . . . . . . . . . . . . . . . 44
3.2 Limitation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
4 GUI for Multi-Sensor Monitoring . . . . . . . . . . . . . . . . . . . . . . . 46
Location Service in Patient-Centric Medical Environment 47
1 Introduction to Location Determination . . . . . . . . . . . . . . . . . . . . 47
2 Review of Algorithm for Location Determination via WiFi Signal . . . . . . 48
2.1 Clustering and Probability Distribution Algorithm . . . . . . . . . . 49
2.2 K- Nearest Neighbor Algorithm . . . . . . . . . . . . . . . . . . . . 51
2.3 Nearest Neighbor Mean Algorithm (NNM) . . . . . . . . . . . . . . 52
2.4 Complexity and Memory Capacity Analysis . . . . . . . . . . . . . 53
3 Location Service in Patient-Centric Medical Environment . . . . . . . . . . . 53
3.1 Offline Training Phase . . . . . . . . . . . . . . . . . . . . . . . . . 54
3.2 Discussion about Amount of Training Data . . . . . . . . . . . . . . 55
3.3 Discussion about Training Position Resolution . . . . . . . . . . . . 57
3.4 Discussion about K in KNN Algorithm . . . . . . . . . . . . . . . . 58
3.5 Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
4 Outdoor Location Service . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
Conclusion and FutureWorks 63
1 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
2 Future Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

                                

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