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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 黃天偉 | zh_TW |
| dc.contributor.advisor | Tian-Wei Huang | en |
| dc.contributor.author | 林宜賢 | zh_TW |
| dc.contributor.author | Yi-Hsien Lin | en |
| dc.date.accessioned | 2023-06-14T16:21:09Z | - |
| dc.date.available | 2023-11-09 | - |
| dc.date.copyright | 2023-06-14 | - |
| dc.date.issued | 2022 | - |
| dc.date.submitted | 2002-01-01 | - |
| dc.identifier.citation | [1] J. C. Lin, “Noninvasive microwave measurement of respiration,” Proc. IEEE, vol. 63, no. 10, pp. 1530-1530, Oct. 1975. [2] M. Ambrosanio, S. Franceschini, G. Grassini and F. Baselice, “A multi-channel ultrasound system for non-contact heart rate monitoring,” IEEE Sensors J., vol. 20, no. 4, pp. 2064-2074, Feb. 2020. [3] H. Abuella and S. Ekin, “Non-contact vital signs monitoring through visible light sensing,” IEEE Sensors J., vol. 20, no. 7, pp. 3859-3870, Apr. 2020. [4] J. C. Y. Lai et al., “Wireless sensing of human respiratory parameters by low-power ultrawideband impulse radio radar,” IEEE Trans. Instrum. Meas., vol. 60, no. 3, pp. 928-938, Mar. 2011. [5] B. Schleicher, I. Nasr, A. Trasser and H. Schumacher, “IR-UWB radar demonstrator for ultra-fine movement detection and vital-sign monitoring,” IEEE Trans. Microw. Theory Techn., vol. 61, no. 5, pp. 2076-2085, May 2013. [6] M. Alizadeh, G. Shaker, J. C. M. De Almeida, P. P. Morita and S. 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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/87561 | - |
| dc.description.abstract | 本論文提出了利用多頻率連續波 (multiple-frequency continuous-wave, MFCW)進行生命體徵偵測的概念。多頻率連續波雷達系統具有應對人體各種生理狀況的能力。根據數學模型，通過分析輸出基頻信號的振幅和頻譜成分，針對不同的胸腔運動振幅，尋找一個該狀況下最佳的偵測載波頻率。此外，也針對了雷達模組的偵測距離進行鏈路分析 (link budget) 計算。數學模型與鏈路計算皆於論文中得到了實驗驗證，理論和實驗結果高度吻合。 在實驗一中，使用一個寬頻接收器前端電路，於 4 GHz 到 30 GHz 的載波頻率之間，驗證了在各種胸腔運動振幅下的生命體徵信號分辨率。實驗結果證明了，在憋氣和在不同強度的呼吸下，個別存在不同的最佳偵測載波頻率。同時，所得的實驗結果與數學模型擁有高吻合度。 應用實驗一中的結果，利用雙頻收發模組開發了一個雙頻偵測流程。雙頻雷達系統的工作頻率為 4.26 GHz 至 4.95 GHz 和 17.06 GHz 至 19.79 GHz。 在實驗二中，模擬了從遠處尋找一生命狀況未知的待測者的情境。實驗過程中，呼吸信號的探測距離可達到 12 公尺，心跳信號的探測距離則可達到 6 公尺。即使用木板或磚牆作為偵測路徑中的障礙物，生命體徵偵測也是可行的。 接著在實驗三中，進行了併行 (concurrent) 雙頻 MFCW 偵測以進行更精確的分析。從併行的偵測結果中，可以通過比較不同載波頻率下的偵測結果來推斷呼吸狀態；此外，通過對集成經驗模態分解（EEMD）和主成分分析（PCA）後的結果進行互相關，可減少呼吸諧波或互調音調的非線性影響，從而實現更準確的心率識別。 接收器前端電路和信號源皆採用台積電 CMOS 180 奈米技術製造，並封裝在Rogers RO4003C 印刷電路板 (PCB) 上。韋瓦第天線由於其寬帶特性，被應用於本論文的各個實驗中。 | zh_TW |
| dc.description.abstract | This dissertation presents a concept of vital-sign detection using multiple frequencies of continuous wave. A multiple-frequency continuous-wave (MFCW) radar system has the ability to cope with various physiological conditions of a human subject. Following the mathematical model, the respective favorable carrier frequencies for detection under different thoracic movements are sought, by analyzing the amplitude and spectral com- position of the output baseband signal. Furthermore, the link budget is calculated for the detection distance of the radar module. Both the mathematical model and the link budget calculation have been verified by experiments in this dissertation, and the theoretical and experimental results are highly consistent. In Experiment 1, the resolution of vital-sign signals from carrier frequency of 4 GHz to 30 GHz under various thoracic movements is verified by using a broadband receiver front-end. The results show that there are different favorable detection carrier frequencies for breath-holding and different intensities of respiration. At the same time, the obtained experimental results are in good agreement with the mathematical model. Applying the results in Experiment 1, a dual-band detection process is developed utilizing the dual-band transceiver module. The frequencies of the dual-band radar system are 4.26 GHz to 4.95 GHz and 17.06 GHz to 19.79 GHz. In Experiment 2, it emulates searching for a subject with unknown vital condition from a distance. During the experiment, the respiratory signal could be detected up to 12 meters, and the heartbeat signal could be detected up to 6 meters. Vital-sign detection was satisfactory even with a wooden plank or brick wall as a barrier in the detection path. Later in Experiment 3, a concurrent dual-band MFCW detection is carried out for more precise analyses. From the concurrent detection results, the breathing status can be inferred by comparing the detection results under different carrier frequencies; Besides, by adopting cross-correlation to the results after the ensemble empirical mode decomposition (EEMD) and principal component analysis (PCA), the nonlinear effects of respiratory harmonics or intermodulation tones are reduced, enabling accurate heart rate identification. The receiver front-end and the signal source are both manufactured by TSMC CMOS 180-nm technology, and packaged on an Rogers RO4003C printed-circuit board (PCB). The Vivaldi antenna is applied to the experiments in this dissertation due to its broadband characteristics. | en |
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| dc.description.tableofcontents | 口試委員會審定書 i 致謝 iii 中文摘要 vii Abstract ix Contents xi List of Figures xv List of Tables xxv Chapter 1 Introduction 1 1.1 Background and Motivation 1 1.2 Contributions 6 1.3 Organization of This Dissertation 8 Chapter 2 Detection Theory and Procedure 11 2.1 Resolution Modeling and Spectral Analysis 11 2.1.1 Modeling of the Radar Detection Results 11 2.1.2 Mean Amplitudes of the Detected Vital-Sign Signals 15 2.1.3 Amplitude Fluctuations of the Detected Vital-Sign Signals 21 2.1.4 Output Baseband Spectrums 23 2.2 Link Budget Calculation 26 2.2.1 Mean Effective RCS of Respiration and Heartbeat 26 2.2.2 Mean Maximum Detection Distance 29 2.2.3 Contribution of Different Kinds of Noise Figures 34 2.3 Detection Procedure 36 Chapter 3 System Architecture 39 3.1 Broadband Receiver System Block 39 3.1.1 A 4-30 GHz CMOS Distributed Amplifier 40 3.1.2 A 4-30 GHz CMOS Down-Conversion Mixer 42 3.1.3 Integrated Circuit and Module of the Broadband Receiver Front-End 43 3.1.4 Baseband Design and Setup 53 3.1.5 Performance of the Whole Receiver 55 3.2 Dual-Band Transmitter System Block 58 3.2.1 An X-band CMOS Phase-Locked Loop (PLL) 59 3.2.2 A 17-20 GHz CMOS Frequency Doubler 62 3.2.3 Auxiliary Buffer Amplifiers 64 3.2.4 Integrated Circuit of the Dual-Band Transmitter 65 3.3 Dual-Band Transceiver Front-End Module 71 3.3.1 Dual-Band On-PCB Power Splitting Network 75 3.3.2 Transmitter Performance of the Dual-Band Transceiver Front-End Module 80 3.3.3 Receiver Performance of the Dual-Band Transceiver Front-End Module 85 3.4 Broadband Vivaldi Antenna 88 Chapter 4 Algorithmic Processing for Vital-Sign Identification 95 4.1 Ensemble Empirical Mode Decomposition (EEMD) 95 4.1.1 Empirical Mode Decomposition (EMD) 95 4.1.2 From EMD to EEMD 104 4.1.3 Classification of Vital-Sign Signals After EEMD 107 4.2 Principal Component Analysis (PCA) 109 4.3 Cross-Correlation 113 Chapter 5 Vital-Sign Detection Experiments 117 5.1 Experiment 1: Broadband Frequency Agile Detection 118 5.1.1 With the Subject Holding Breath 121 5.1.2 With the Subject Breathing Normally 125 5.1.3 With the Subject Breathing Heavily 129 5.1.4 Summary 133 5.2 Experiment 2: Dual-Band MFCW Channel Agile Detection 134 5.2.1 Detection from a Distance in Line-of-Sight 136 5.2.2 Detection with a Barrier Blocking the Path 142 5.2.2.1 A 5-cm Thick Wooden Plank Blocking the Path 142 5.2.2.2 A 17-cm Thick Brick Wall Blocking the Path 145 5.2.3 Channel Agility 147 5.2.4 Summary and Discussion 149 5.2.4.1 Summary of the Detection Process Under Various Conditions 149 5.2.4.2 Theoretical Mean Maximum Detection Distance 152 5.2.4.3 Possible Reasons for the Difference Between Experimental Results and Theoretical Values 155 5.3 Experiment 3: Concurrent Dual-Band MFCW Detection 157 5.3.1 Detection of Various Physiological Conditions 159 5.3.2 Flow of the EEMD-PCA and Cross-Correlation Process 167 5.3.3 Summary 172 Chapter 6 Conclusions and Future Works 175 6.1 Conclusions 175 6.2 Future Works 177 6.2.1 On Hardware 177 6.2.2 On Software 179 6.2.3 On the Vital-Sign Detection Experiment 179 References 181 List of Publications 193 | - |
| dc.language.iso | en | - |
| dc.title | 應用於生理活動偵測之微波/毫米波雙頻段智慧型頻率追蹤雷達研究 | zh_TW |
| dc.title | Research on Microwave/Millimeter-Wave Dual-Band Smart Frequency Agile Radar for Physiological Movement Detection | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 111-1 | - |
| dc.description.degree | 博士 | - |
| dc.contributor.oralexamcommittee | 洪子聖;張盛富;曾昭雄;張鴻埜;陳士元;劉怡君;蔡政翰;張譽騰 | zh_TW |
| dc.contributor.oralexamcommittee | Tzyy-Sheng Horng;Sheng-Fuh Chang;Chao-Hsiung Tseng;Hong-Yeh Chang;Shih-Yuan Chen;Yi-Chun Liu;Jeng-Han Tsai;Yu-Teng Chang | en |
| dc.subject.keyword | 都卜勒雷達,生命體徵偵測,互補式金氧半場效電晶體,寬頻接收機,雙頻收發機,頻率捷變,多頻率連續波雷達,併行多頻率連續波偵測,集成經驗模態分解,主成分分析,互相關, | zh_TW |
| dc.subject.keyword | Doppler radar,vital-sign detection,CMOS,broadband receiver,dual-band transceiver,frequency agility,multiple-frequency continuous-wave (MFCW) radar,concurrent MFCW detection,ensemble empirical mode decomposition (EEMD),principal component analysis (PCA),cross-correlation, | en |
| dc.relation.page | 196 | - |
| dc.identifier.doi | 10.6342/NTU202204274 | - |
| dc.rights.note | 未授權 | - |
| dc.date.accepted | 2022-10-20 | - |
| dc.contributor.author-college | 電機資訊學院 | - |
| dc.contributor.author-dept | 電信工程學研究所 | - |
| 顯示於系所單位： | 電信工程學研究所 | |
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