本論文利用光的吸收特性在心血管循環系統(Cardiovascular circulatory system)中，血液及血管的變化造成穿透光強度的不同來做為訊號的依據，進而演算出生理系統的相關性。 在演算的部分，本研究引入連續小波轉換(Continuous Wavelet Transform, CWT)，可以觀察到即時的動態頻譜分析(dynamic spectrum analysis)，進而方便觀測出即時的心率變異(Heart Rate Variability, HRV)、呼吸行為和血液在血管中的流量走勢，並使用深呼吸和一般呼吸兩種呼吸方式當作範本進行探討。 深呼吸的呼吸深度較深且吸氣和吐氣的時間間隔較大，可以提供明顯有力的指標；一般呼吸屬於淺呼吸，有較為明顯的基線飄移(base line shift)，不易觀察出呼吸行為的差異。以往的論文發表以傅立葉頻譜(Fourier spectrum)的呼吸頻率來找出呼吸速度，但是在實際時間上卻有相位差異的問題存在，無法正確計算出呼吸運動的時間。本論文藉由心率差異來分離出吸氣和吐氣的行為並且還原出真實吸氣和吐氣的行為時間關係，並提出心率變異(HRV)和呼吸行為的動態關係。 ;In this thesis, we use Photoplethysmography (PPG) to absorb the light intensity in the cardiovascular circulatory system. The different of light intensity can calculate the relevance of the physiological system In the Algorithm, this paper introduces the continuous wavelet transform (CWT), which can observe the real-time dynamic spectrum analysis, and then we can easily to observe the heart rate variability (HRV), respiratory behavior and the trend of blood in the blood vessels. In this thesis, we prefer to use deep breathing and normal breathing two breathing methods as a template to explore. The depth of the deep breathing and breathing time interval is larger. It can provide a clear and effective indicators; normal breathing is shallow breathing, baseline shift is affect by more autonomic nervous system, and it is difficult to observe the difference in respiratory behavior. In this thesis, the differences of inspiration and expiration are separated by the heart rate variability and restore the real time behavior of inspiration and expiration.
