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病理心电信号的Jensen-Shannon divergence分析

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  • 国家科技期刊平台
  • NETL
  • NSTL
  • 万方数据
目的 研究快速区分不同病理心电信号的算法是当前临床医学诊断的研究热点之一.方法 本文采用基于Jensen-Shannon divergence的复杂度分析方法,从MIT-BIH标准数据库中提取正常窦性心率、房性早搏、窦性心动过缓信号,分别计算它们的复杂度.结果 正常心率信号复杂度最高,窦性心动过缓信号次之,房性早搏最低.方差检验结果表明,此方法得出的3种信号的复杂度具有显著性差异.结论 病理心电信号的Jensen-Shannon divergence分析对临床医学检测和诊断房性早搏、窦性心动过缓信号有很好的借鉴意义.
Complexity analysis of pathological ECG signal based on Jensen-Shannon divergence
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.

Jensen-Shannon divergencecomplexityatrial premature contractionsinus bradycardia signalECG signal

许欢、孟浩、王俊

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南京邮电大学地理与生物信息学院图像处理与图像通信重点实验室,南京210003

Jensen-Shannon divergence 复杂度 房性早搏 窦性心动过缓 电信号

国家自然科学基金国家自然科学基金国家自然科学基金江苏省自然科学基金江苏省自然科学基金

612710826120102961102094BK2011759BK2011565

2012

10.3969/j.issn.1002-3208.2012.06.04

北京生物医学工程
北京市心肺血管疾病研究所

北京生物医学工程

CSTPCD
影响因子：0.474
ISSN：1002-3208
年,卷(期)：2012.31(6)
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