臺灣博碩士論文加值系統

目前具心跳量測功能之穿戴裝置使用的生物感測器以光電感應器為主，僅可藉由光反射率測量血氧量，但脈搏波為一種壓力波，所以光電感應器不適用於脈搏波的量測，因此光電感測器僅可獲得血氧量的資料，而無法量測到壓力波資料。而中醫師目前切診是以脈搏的壓力波來獲得訊息，醫師於切診過程中對六部穴位施加壓力，依血液循環共振理論，斷定血液流經各臟腑所造成的共振波、各部穴位的壓力及心跳頻率，以確定身體的健康狀況。因此，本研究利用壓力及震動之感測器，進行生理訊號的量測並分析，以取代光電感應器。但環境中有諸多干擾訊號會影響量測分析結果，因此本研究也針對干擾訊號設計硬體電路，其中包含儀表放大器、帶拒濾波器、低通濾波器及高通濾波器等電路。再以微處理器執行快速傅立葉轉換來分析脈搏波訊號，最後以電腦軟體將量測的結果儲存，同時顯示脈搏波的頻譜，以提供醫師進行個案生理疾病之研究參考。

Nowadays, the electronic wearable device which provides heart rate measurement service uses an internal photoelectric sensor to measure it. The photoelectric sensor can only measure the arterial oxygen by measuring the amount of reflected light. However, it is not suitable for measure the real pulse wave what we care in eastern medicine. The reason is that the pulse is a kind of pressure wave and the photoelectric sensor is not really deigned for measuring pressure. The doctor puts some pressure on those six acupuncture points when measuring pulse. Then, according to the blood resonance theory diagnoses the disease of viscera and heart rate. So we use a pressure sensor instead of a common photoelectric sensor to measure the pulse wave. Another problem is that any kind of interference makes the result unreliable. So we will aim to design a hardware signal conditioning unit includes instrumentation amplifier, band-stop filter, low-pass and high-pass filters. Then, a microprocessor translates the pulse wave to spectrum data using fast Fourier transform. Finally, this system will send the result that is measured currently to a computer. The computer runs a program which can repaint the spectrum graph and store the result. This is good for doctors to do individual case research and tracing diseases. It also makes users have a habit to pay attention to their health.

摘要 I
Abstract II
Acknowledgement III
Table of Contents IV
List of Tables VI
List of Figures VII
Chapter 1 Introduction 1
1.1 The Idea 1
1.2 Literature Survey 2
1.3 Thesis Architecture 9
Chapter 2 Science of Pulse 11
2.1 Researches of Pulse 11
2.2 Analysis Method 12
2.3 Measuring Method 14
2.4 Distinguish Between the Healthy and the Ill Pulse 16
2.5 Read the Pulse Graph 21
2.6 The Particular Pulse We Cannot Analysing by Pulse Graph 23
2.7 Clinical Pulse Graph 24
Chapter 3 System Architecture and Achievement 33
3.1 Hardware Architecture 34
3.2 Firmware Architecture 44
3.3 Software Architecture 47
Chapter 4 System integration and Experiment 52
4.1 Experimental Procedure 55
4.2 Experiment result 55
Chapter 5 Conclusions and Future Work 61
5.1 Advantage of this system 61
5.2 Future Work 62
Reference 63
Appendix 67
List of Abbreviations 67
List of Symbols 68
Functions 69
Special Function Registers of Atmega328 69

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