生命體徵的監測是一種重要的醫療方法，有助於醫療人員判斷患者的身體狀況，尤其常用於檢查心律不整或睡眠呼吸中止，但傳統的接觸式測量，除了造成患者不適，也增添醫療人員的工作量。
為了改善接觸式測量的缺點，研究者們將目光轉向非接觸式的測量方式，患者不再需要穿戴裝置，醫療人員也可以長時間監控患者的狀況，然而非接觸式的測量方式使訊號容易受到外在干擾，嚴重影響測量數據的精確度。
在本研究利用FMCW雷達的電磁波監測受測者的心跳訊號，並在測試過程中設計了一系列的操作變因與控制變因，試著去找出影響雷達訊號精確度的因素。
我們根據實驗結果進行比較，找出了影響較大的因素：環境與擋住胸口的動作，並成功排除了部分不會干擾測試的行為，讓FMCW雷達在之後的應用能夠更加靈活。

The monitoring of vital signs is an important medical method that helps medical staff judge the patient’s physical condition. It is especially used to check for arrhythmia or sleep apnea. However, traditional contact measurement not only causes discomfort to the patient, but also adds workload to the medical staff.
In order to improve the shortcomings of contact measurement, researchers have turned their attention to non-contact measurement methods. Patients no longer need to wear devices, and medical staff can continuously monitor the patient’s condition. However, non-contact measurement methods make the signal vulnerable to external interference, and seriously affects the accuracy of the measurement data.
In this study, we used the electromagnetic waves of the FMCW radar to monitor the heartbeat signal of the subject, and designed a series of independent variables and control variables during the test, trying to find out the factors that affect the accuracy of the radar signal.
We compared the experimental results and found out the factors that have a greater impact: the environment and the actions that block the chest, and successfully eliminated some behaviors that would not interfere with the test, making the FMCW radar more flexible in the future application.

摘要---II
ABSTRACT---III
圖次---VI
表次---VII
第一章 緒論---1
1.1 研究背景與動機---1
1.2 論文架構---2
第二章 相關研究---3
第三章 系統架構---5
3.1 硬體介紹---5
3.1.1 AWR1642---5
3.1.2 DCA1000---6
3.1.3 血氧濃度機---7
3.2 訊號處理---8
3.3 雷達參數設定---11
第四章 實驗與資料庫建構---12
4.1 實驗設計---13
4.1.1 距離變因---13
4.1.2 角度變因---14
4.1.3 環境變因---17
4.1.4 動作變因---18

4.2 實驗結果分析---20
4.2.1 基於頻譜分析距離衰減影響---20
4.2.2 基於頻譜分析角度失真影響---22
4.2.3 基於頻譜分析障礙物干擾影響---25
4.2.4 基於頻譜分析動作干擾影響---27
第五章 結論與未來工作---31
參考文獻---32

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[13] mmWave Vital Signs Lab :
https://training.ti.com/mmwave-vital-signs-lab?context=1128486-1139155-1128631
[14] AWR 1642 Single-Chip 76-GHz to 81-GHz Automotive Radar Sensor Evaluation Module :
https://www.ti.com/tool/AWR1642BOOST
[15] DCA 1000 EVM Real-Time Data-Capture Adapter for Radar Sensing Evaluation Module :
https://www.ti.com/tool/DCA1000EVM
[16] ACARE AE-XX Finger Pulse Oximeter: https://www.acaretech.com/product_872346.html