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一種基于幾何特征的ECG波形識別算法

An ECG waveform recognition algorithm based on geometric characteristics

作者: 李鋒  陳美麗                          
單位:                                 東華大學(xué)計算機(jī)學(xué)院(上海201620)            
關(guān)鍵詞:                               ECG;波形識別;幾何特征;QRS波群              
分類號:
出版年·卷·期(頁碼):2015·34·3(261-266)
摘要:

目的  ECG自動分析系統(tǒng)由兩部分組成: 波形識別和智能診斷。在實際應(yīng)用中, 心電波形識別是該系統(tǒng)的關(guān)鍵。波形識別的精確性和可靠性決定了心臟病診斷的可靠性。為提高波形識別的速率及準(zhǔn)確度,本文提出一種基于幾何特征的ECG波形識別算法。方法 首先利用數(shù)字濾波算法對信號進(jìn)行預(yù)處理,提高信號的信噪比,然后通過改進(jìn)的二階導(dǎo)數(shù)計算出數(shù)據(jù)的幾何特征:點的斜率和運動趨勢,并在此基礎(chǔ)上,結(jié)合ECG波形的實際物理特征,利用算法實現(xiàn)T波、P波、QRS波群的起點、終點以及波峰波谷的自動識別。結(jié)果 統(tǒng)計分析結(jié)果表明,本算法能夠快速高效地識別ECG波形。同時將該算法與其他當(dāng)前各種ECG波形識別算法進(jìn)行對比,該識別算法在識別的精確性與陽性預(yù)測值方面具有更好的性能。結(jié)論 本文提出的基于幾何特征的ECG波形識別算法可以進(jìn)一步提高當(dāng)前ECG波形識別算法的性能。

Objective ECG analysis diagnosis system mainly consists of two phases: waveform recognition and intelligent diagnosis. Accuracy and reliability of ECG waveform recognition determine the diagnosis and treatment of heart disease. A waveform recognition algorithm based on geometric characteristics is proposed in this paper to improve the detection rate and accuracy of waveform recognition. Methods Firstly, signals are preprocessed to improve noise ratio by digital filtering algorithm. Secondly, we calculate certain geometric characteristics such as the slope and the movement tendency of points with improved second derivative. Finally, we can automatically recognize the onset, the offset, the peak and the trough of T wave, P wave, QRS complex with the actual physical characteristics of ECG waveform on the basis of the previous results. Results Statistical analysis shows that our method can recognize the ECG wave fast and effectively. We also compare this method with other ECG waveform recognition algorithms. The results indicate that the proposed method results in better performance in the sensitivity (Se) and positive predictive (PP) than other methods. Conclusions The proposed method makes improvement on current ECG waveform recognition methods.

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