簡單有效的特徵點選取演算法及其應用於心跳種類的辨識

本篇論文提出簡單有效的特徵點選取法及其應用於心跳種類的辨識。特徵點選取，本論文提出了主成份分析法(PCA)及區間交集法(RIM)二種演算法。心跳種類的辨識，本論文提出了模糊邏輯法(Fuzzy logic)。本論文所提之演算法，有方法簡單、辨識心跳種類的速度快、高的正確辨識率、及高的可靠度等優點。本論文是由以下的三大部份組成，分別是(i) QRS extraction stage：使用Difference Operation Method (DOM)法尋找心電圖中的QRS複合波；(ii) qualitative features stage：使用主成份分析法(PCA)及區間交集法(RIM)；(iii) classification stage：使用模糊邏輯法辨識心跳的種類。經過多次的實驗，正確辨識率平均可達94.03%以上。

關鍵字

主成份分析法(PCA) ；模糊邏輯法(Fuzzy logic) ；特徵點選取(feature selection)

並列摘要

This dissertation proposes a simple and reliable feature selection algorithm for ECG signals which can be applied on heartbeat case determining. A well-established technique, Principal Component Analysis (PCA) and Range-Intersection method (RIM) are employed for qualitative feature selection in this study. Determination of heartbeat case is carried out by fuzzy logic method. The proposed method has the advantages of simple mathematic computations, high speed, low memory space, good detection results, and high reliability. This study consists of three major stages: (i) QRS extraction stage for detecting QRS waveform using the Difference Operation Method (DOM); (ii) qualitative features stage for qualitative feature selection from ECG signals using the PCA and RIM methods; and (iii) classification stage for determining patient’s heartbeat cases using fuzzy logic. Experimental results show that the total classification accuracy is 94.03% for method by using fuzzy logic.