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研究生(外文):Yuan-Po Chen
論文名稱(外文):Optimum Analysis of Wavelet Algorithm combined with Wireless Sensor Network
指導教授(外文):Gwo-Jia Jong
外文關鍵詞:electrocardiogramwireless senor networkreceived signal strength indicatior
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近年來,ZigBee應用於無線感測網路(WSN)發展技術層面日漸廣泛的增長,本論文對於WSN 裝置在可利用估算各個裝置所進行路徑、射頻訊號強度指示(RSSI)及服務品質(QoS)等參數功能,達到最佳化無線網路系統需求。
本系統未來可擴展至醫院與居家照護(Home Care)之需求,利用遠距醫療系統,整合無線行動通訊網路系統技術,達到之無所不在(Ubiquitous)行動監控應用。
In this thesis, we adopt the wavelet algorithm combined compression process of biomedical signal. The main functions of biomedical signal sensor acquire electrocardiogram (ECG) signal and waveform. The correlation bio-information is transmitted the indoor positioned and traced locations of biomedical module by using Zigbee nodes. The wavelet algorithm is operated to separate measure signal and improve the system time-frequency (TF). The data acquisition (DAQ) system is operated by remote device to implement the biomedical signal monitor, measure and analysis functions.
In recent years, the ZigBee system has been applied to the wireless senor network (WSN) development technology. The WSN devices are estimated individual route, received signal strength indicatior (RSSI) and quality of service (QOS) parameter functions for obtaining the optimal requirement for the wireless network system.
The future work of this system can be developed and integrated the hospitals and home care requirements using long-distance medical system. It is combined with the wireless mobile communication network system technique for ubiquitous and mobile monitor applications.
Abstract in Chinese i
Abstract ii
Acknowledgements iii
Contents iv
List of Figures vii
List of Tables viii
Abbreviations ix
Chapter 1 Introduction 1
1.1 Motivation 1
1.2 Organization of this Thesis 2
Chapter 2 ZigBee Overview 3
2.1 Introduction 3
2.2 ZigBee Stack Architecture 3
2.3 IEEE 802.15.4 4
2.3.1 Physical Layer 5
2.3.2 Medium Access Control Layer 6
2.4 ZigBee Standard 7
2.4.1 Network Layer 7
2.4.2 Application Support Sub-Layer 8
2.4.3 Application Framework 9
2.4.4 ZigBee Device Object and ZDO Management Plane 10
2.4.5 Security Service Provider 10
2.5 Location Engine 11
2.5.1Location Engine Operation 11
Chapter 3 Time-Frequency Analysis 13
3.1 Fourier Transform 13
3.2 Wavelet Transform 15
3.3 Discrete Time Wavelet Transform 17
3.4 Least Mean Square (LMS) Algorithm 20
Chapter 4 System Integration 23
4.1ECG 23
4.1.1Seach Boundary Coordinates 24
4.1.2 The Standard Lead System 27
4.2 Biomedical Signals Measurement Device 28
4.3 Discrete Time Wavelet Transform of ECG 30
4.4 ECG used Least Mean Square Algorithm 31
4.5 System Configuration 33
4.5.1 Body Area Network (BAN) 33
4.6 Optimum Window Filter 34
Chapter 5 Implemented Results 36
5.1 Measurement Results of Real-Time Waveform 36
5.1.1 Wavelet Transform of ECG 37
5.1.2 Least Mean Square of ECG 38
5.2 Zigbee Location System 39
5.2.1 Safety of Home-Care System 40
5.2.2 Emergency of Home-Care System 42
Chapter 6 Conclusions 43
References 44
List of Publications 49
Biography 50
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[19] Azzedine Boukerche, Horacio A.B.F. Oliveira, Eduardo F. Nakamura, and Antonio A.F. Loureiro, “A Novel Location-Free Greedy Forward Algorithm for Wireless Sensor Networks”, Communications, 2008. ICC '08. IEEE International Conference on, Brazil, pp. 2096-2101, May 2008.
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[24] Zhao Jiyin, Li Jianpo, Zheng Ruirui, Sun Junxiang, “Application of Variable Step LMS Algorithm Based on Iterative Time in ECG Signal Abstraction”, Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International Conference on, China , pp.2266-2269, May 2008.
[25] Peter Strobach, Klaus Abraham-Fuchs, Wolfgang Harer, “Event-synchronous cancellation of the heart interference in biomedical signals”, Biomedical Engineering, IEEE Transactions on , pp. 343-350 , April 1994.
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