Heart Rate Variability (HRV)生理訊號分析已被廣泛運用在醫學臨床診斷上，然而在心電圖圖形中，HRV分析無法取得所有的生理資訊。有鑑於此，本文提供一種新的R-Wave Amplitude Variability (RAV)生理訊號參數分析法，可從ECG中取得不同於HRV分析所法取得之生理訊號。RAV生理訊號參數分析法是取出ECG中每個心跳的R波振幅，再進行傅立葉轉換到頻域空間，分析其功率頻譜，從不同的頻率範圍之功率當中，定義出能代表生理訊號的參數，並進行統計。另外同時使用線性迴歸分析的方法，分析HRV及RAV生理訊號之間的線性相關度，以比較兩種分析方法的異同。在20位實驗樣本四種不同姿勢中，我們得到右側臥之RAV參數在統計上和左側臥、仰臥、坐姿等三種姿勢有差異；迴歸分析的結果則顯示，兩種分析方法所得的結果有部分線性相關度佳，而有部分關聯性差。因此我們認為這種新的分析方法有別於HRV分析方法，且確實可用於臨床研究。Analysis of HRV is generally used in clinical diagnosis. But HRV method could not get full physiological information from ECG. Therefore, This thesis suggested a new method - R-wave amplitude variability (RAV), which could find physiological information from ECG that differs form HRV. The way to analyze RAV physiological parameter is to get R-wave amplitude from each heart beat in ECG, useing Foureir transfrom transferd to frequency domain and analyzed its power spectrum. Then we defined physiological parameter which could represented physiological status from power spectrum by different frequency range, and proceed statistical analysis. Besides, we use linear regression method to check the linear correlation between HRV and RAV to confirm the two analytic method is different. In 20 samples at four differnet posture, we find human at right decubitus is much different form the other posture; and some parameter of RAV and HRV have better linear correlation and the other are worse. We concluded that the RAV method differs from HRV method and could be used in clinical diagnosis.
