生理訊號擷取系統設計與心電圖之前置分析

Abstract

本篇論文主要分成兩部分。在第一部份中，基於本研究室目前對於禪定生理訊號的研究，因將受限於硬體的緣故，主要是針對腦電波的研究與探討。為了進一步了解人體的生理現象在禪定中的變化，和生理訊號彼此間的關連性，所以必須架設另一套擷取系統。此系統在硬體上主要包含了心電圖、皮膚阻抗和血氧濃度三套放大器還有A/D卡，並可透過同步觸發器來解決和腦電波錄製系統同步的問題。整個硬體建構在Labview軟體的平台上，以便於程式的開發擴充與維護，此外這個軟體還有一個優點就是對於使用者介面的開發非常的容易。 在第二部分中，主要針對心電圖訊號的前置分析。首先是對於心電圖R波的偵測去發展一個演算法，偵測R波的目的在於求出心跳變異率和心電圖時域分割的對準點。分割後的心電圖經由頻域或時域的分析比較可以用於禪定生理現象改變的一個參考指標。期望能為研究室日後對於腦電波以外生理訊號的發展和研究立下基礎。

This thesis includes two parts. In Part I, due to the hardware limitation in our laboratory, the research work has been focused on the EEG (electroencephalograph) signal analysis. In order to explore more physiological phenomena during meditation and understand the correlation among different signals, we need to design and implement a data acquisition system capable of recording a number of physiological signals. This system includes three biological-signal amplifiers and one A-to-D interface card. The three amplifiers are used to measure the ECG (electrocardiograph), skin conductance, and blood oxygen saturation, respectively. This system and the NeuroScan EEG recording system can be triggered simultaneously by a switch to synchronize both systems. All of the hardware control is set up on the bench of Labview software for convenience of programming development and maintenance. In addition, the development of man-machine interface is straightforward using the Labview software. Part II of the thesis is devoted to the preprocessing of ECG signal. First, we aim to design an algorithm for R wave detection. Next, the ECG signal is segmented, based on the R-wave detection, to form a 2D matrix. The results can be further analyzed, in both time and frequency domains, by applying sophisticated DSP (digital signal processing) methods. This study will promote the understanding of more physiological states in meditation.