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系統識別號 U0026-1505201310104500
論文名稱(中文) 連續小波轉換應用於非接觸式生命徵象信號分析
論文名稱(英文) Analysis of Non-contact Vital Sign Signals Using Continuous Wavelet Transform
校院名稱 成功大學
系所名稱(中) 電機工程學系碩博士班
系所名稱(英) Department of Electrical Engineering
學年度 101
學期 2
出版年 102
研究生(中文) 沈彥佑
研究生(英文) Yen-Yu Shen
學號 n26001513
學位類別 碩士
語文別 英文
論文頁數 70頁
口試委員 指導教授-李國君
口試委員-雷曉方
口試委員-郭致宏
中文關鍵字 數位信號處理  都普勒雷達  生命徵象  心率  心率變異分析  時頻分析  連續小波轉換  健康照護監控 
英文關鍵字 DSP  Doppler radar  heart rate  heart rate variability (HRV)  joint time-frequency analysis (JTFA)  continuous wavelet transform (CWT)  healthcare monitoring 
學科別分類
中文摘要 本論文提出一個自動化電腦輔助都普勒雷達的生命徵象 (呼吸、心跳) 健康照護監測數位處理器。含有心臟跳動和呼吸特徵之電壓波形信號藉由一個帶通濾波器來濾得心跳信號。 所提出的方法,結合連續小波變換(CWT)和峰值偵測,可自適應的為每個相位調變得到的都普勒雷達信號計算心率。 藉由在醫學上的成熟發展的心電圖的輔助,我們可以更完善的實現非接觸式生命徵象監測系統。此外利用心率變異(HRV)分析來做心肺疾病的預測。 實驗結果的呈現可看出,我們提出的演算法不僅提供了精確的心率計算,而且可以分析評估心率變異(HRV),進而實現非接觸式生命徵象監測系統。
英文摘要 An automatic computer-aided digital signal processor for Doppler radar vital signs healthcare monitoring is described. A voltage waveform signal containing heart-beat and respiration signatures are band-pass filtered for the heart signal. The proposed method, combination of continuous wavelet transform (CWT) and peak finding, is used to adaptively detect heart-beat rate for each of these phase modulated Doppler radar signals. Involving in electrocardiogram, well-developed medical aid, realizes a complete non-contact vital signs monitoring system. An investigation of heart rate variability (HRV) measurements is adopted for the cardiopulmonary disease prognosis. Experimental results show that the proposed algorithm not only provides an accurate heart rate detection but also be able to evaluate heart rate variability (HRV).
論文目次 摘 要 i
Abstract ii
誌 謝 iv
Table of Contents vi
List of Tables ix
List of Figures x
Chapter 1 Introduction 1
1.1 Introduction 1
1.2 Motivation 2
1.2.1 Healthcare Monitoring in Millimeter-Wave Life Detection System (MLDS) 2
1.3 Organization of this Thesis 2
Chapter 2 Background Information 3
2.1 Radar Measurement of Chest Movement 3
Chapter 3 Surveys of Medical Information and Related Works in the Literatures 7
3.1 Physiological Motion and Medical Information 7
3.1.1 Heart Motion 8
3.1.1.1 Electrical and Mechanical Events of the Heart 10
3.1.1.2 Chest Wall Motion due to Heart 12
3.1.1.3 Summary of Heart Motion 13
3.1.2 Respiration System Motion 13
3.1.2.1 Chest Wall Motion due to Breathing 14
3.2 Heart Rate Variability 16
3.2.1 Measurement of HRV 16
3.2.1.1 Time Domain Measures 16
3.2.1.2 Frequency Domain Measures 18
3.2.2 Change of HRV related to Clinical Pathologies 20
3.2.3 Summary of HRV measurement 21
3.3 Signal Separation(Noise removal, Heart signal isolation) 21
3.3.1 Filtering 22
3.4 Heart Rate Finding 24
3.4.1 Peak Detection 24
3.4.2 Autocorrelation 24
3.4.3 Fourier Analysis 25
3.4.4 Continuous Wavelet Transform (CWT) 26
3.4.5 Conclusions 30
Chapter 4 Proposed Algorithms 31
4.1 Signal Process and Healthcare Monitoring in Non-contact Vital Signs 31
4.1.1 Block Diagram 31
4.2 Heart Signal Extraction 33
4.3 Heart Rate Detection 42
4.3.1 Continuous Wavelet Transform (CWT) Analysis of NCVS Signal 42
4.3.1.1 Scale Index Determination 44
4.3.1.2 Translation Parameter 48
4.3.2 Peak Detection 49
4.4 Signal Matching and Vital Signs Monitoring 53
4.4.1 Time Matching Process 53
4.4.2 Vital Signs Monitoring 56
4.5 Experimental Results and Comparisons 59
Chapter 5 Conclusions and Future Work 64
5.1 Conclusions 64
5.2 Future Work 65
References 66
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