北京生物醫(yī)學(xué)工程

病理心電信號的Jensen-Shannon_divergence分析

Complexity analysis of pathological ECG signal based on Jensen-Shannon divergence

作者：許歡孟浩王俊

單位：南京郵電大學(xué)地理與生物信息學(xué)院圖像處理與圖像通信重點(diǎn)實(shí)驗(yàn)室(南京210003)

關(guān)鍵詞： Jensen-Shannon divergence；復(fù)雜度；房性早搏；竇性心動過緩；電信號

分類號：

出版年·卷·期（頁碼）：2012·31·6（565-569）

摘要：

研究快速區(qū)分不同病理心電信號的算法是當(dāng)前臨床醫(yī)學(xué)診斷的研究熱點(diǎn)之一。方法本文采用基于Jensen-Shannon divergence的復(fù)雜度分析方法，從MIT-BIH標(biāo)準(zhǔn)數(shù)據(jù)庫中提取正常竇性心率、房性早搏、竇性心動過緩信號，分別計(jì)算它們的復(fù)雜度。結(jié)果正常心率信號復(fù)雜度最高，竇性心動過緩信號次之，房性早搏最低。方差檢驗(yàn)結(jié)果表明，此方法得出的3種信號的復(fù)雜度具有顯著性差異。結(jié)論病理心電信號的Jensen-Shannon divergence分析對臨床醫(yī)學(xué)檢測和診斷房性早搏、竇性心動過緩信號有很好的借鑒意義。

Objective Algorithm research on high-speed diagnosis of pathological ECG is one of the current research hotspots in clinical diagnosis. Methods In this paper,complexity measure based on Jensen-Shannon divergence was used to compute complexity of the ECG signals,which include normal sinus rhythm,atrial premature contraction (APC) and sinus bradycardia (SBR) signals from the MIT-BIH standard database. Results The results showed that the three kinds of signals had different complexity measures. Normal sinus rhythm had the highest complexity,followed by SBR signals and APC signals. The variance test indicated that this analysis could disclose the significant differences among these three signals’ complexity. Conclusions This complexity analysis based on Jensen-Shannon divergence is a good reference for clinical detection and diagnosis of APC and SBR signals.

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