- 學位論文
利用希伯特黃轉換來探討手術過程中病患的血流變異和心率變異
Hilbert-Huang Transform Analysis Applied to the Patients’ Blood flow variability and Heart rate variability during surgery
摘要
麻醉深度的判定，一直都沒有明確的界定，除了從病人基本的生理訊號取得外還要經麻醉醫師多年來的經驗配合來給予適當的給藥濃度，才能使病人得到安全舒適的麻醉過程。近年來許多研究利用心率變異來表示自主神經做動的情形，以此做為麻醉深度的判斷，但由於心跳會因為麻醉藥物、呼吸速率和手術中使用電刀所產生的雜訊所影響，帶給麻醉醫師錯誤的訊息。 本研究的目的是希望能利用工程理論來分析病患在全身麻醉過程中，血流變異和心率變異的變化。當心率變異在某些情況下無法表現出病患的身體狀況時，可以用血流變異取代，輔助麻醉醫師能更了解病人的真實狀況與特性，增加麻醉過程的安全性。 本研究將收集20位接受耳鼻喉手術和10位接受腹腔手術的病人在整個開刀過程的生理訊號，然後用希伯特黃轉換來分析病患的血流變異和心率變異。並且證明： 1. 在施打麻醉藥Atropine後，血流變異受到麻醉藥物影響較心率變異小。 2. 在腹腔手術中執刀醫生使用電刀的情況下，血流訊號所受到的干擾較心跳訊號小。
並列摘要
There’s no specific definition of depth of anesthesia (DOA). It is obtained from patient’s basic physiological signal and the anesthetist’s experience for many years in order to offer proper medicine i.e. give the patient the best and safe anesthesia process. In the past, a lot of studies indicated that heart rate variability (HRV) is a recognized parameter for assessing autonomous nervous system activity. Therefore, HRV can be an indication of DOA. However, heartbeat can be affected by anesthesia drugs, breathing rate and electric influence by operating electric knife. These reasons may bring anesthetist wrong information. The purpose of this research is to use engineering analysis to analyze blood flow variability (BFV) and HRV during anesthesia. When HRV can’t present the patient’s states in some situations, BFV can replace HRV. We help anesthetists to know the patient’s truly states and characteristics, and increase the security of the anesthesia process. This research collects the physiological signals from 20 patients who have accepted ears, nose, throat (ENT) surgery and 10 patients who have accepted the abdominal surgery. Then we use Hilbert-Huang Transform (HHT) to analyze the data and find out the changes of BFV and HRV. Finally, the results have been shown as follows: 1. After injecting Atropine, BFV is less affected than HRV. 2. When the doctor use electric knife to stop bleeding, blood flow signal is less influenced by electricity than ECG.