Karmakar Chandan, Udhayakumar Radhagayathri K, Palaniswami Marimuthu
Annu Int Conf IEEE Eng Med Biol Soc. 2015;2015:5207-10. doi: 10.1109/EMBC.2015.7319565.
Heart rate complexity analysis is a powerful non-invasive means to diagnose several cardiac ailments. Non-linear tools of complexity measurement are indispensable in order to bring out the complete non-linear behavior of Physiological signals. The most popularly used non-linear tools to measure signal complexity are the entropy measures like Approximate entropy (ApEn) and Sample entropy (SampEn). But, these methods become unreliable and inaccurate at times, in particular, for short length data. Recently, a novel method of complexity measurement called Distribution Entropy (DistEn) was introduced, which showed reliable performance to capture complexity of both short term synthetic and short term physiologic data. This study aims to i) examine the competence of DistEn in discriminating Arrhythmia from Normal sinus rhythm (NSR) subjects, using RR interval time series data; ii) explore the level of consistency of DistEn with data length N; and iii) compare the performance of DistEn with ApEn and SampEn. Sixty six RR interval time series data belonging to two groups of cardiac conditions namely Arrhythmia' and NSR' have been used for the analysis. The data length N was varied from 50 to 1000 beats with embedding dimension m = 2 for all entropy measurements. Maximum ROC area obtained using ApEn, SampEn and DistEn were 0.83, 0.86 and 0.94 for data length 1000, 1000 and 500 beats respectively. The results show that DistEn undoubtedly exhibits a consistently high performance as a classification feature in comparison with ApEn and SampEn. Therefore, DistEn shows a promising behavior as bio marker for detecting Arrhythmia from short length RR interval data.
心率复杂性分析是诊断多种心脏疾病的一种强大的非侵入性方法。为了揭示生理信号的完整非线性行为，非线性复杂性测量工具不可或缺。最常用的测量信号复杂性的非线性工具是近似熵（ApEn）和样本熵（SampEn）等熵度量。但是，这些方法有时会变得不可靠且不准确，特别是对于短长度数据。最近，引入了一种称为分布熵（DistEn）的新型复杂性测量方法，该方法在捕获短期合成数据和短期生理数据的复杂性方面表现出可靠的性能。本研究旨在：i）使用RR间期时间序列数据，检验DistEn区分心律失常患者与正常窦性心律（NSR）受试者的能力；ii）探索DistEn与数据长度N的一致性水平；iii）比较DistEn与ApEn和SampEn的性能。两组心脏疾病（即“心律失常”和“NSR”）的66个RR间期时间序列数据已用于分析。对于所有熵测量，数据长度N从50到1000次心跳不等，嵌入维度m = 2。对于数据长度分别为1000、1000和500次心跳的情况，使用ApEn、SampEn和DistEn获得的最大ROC面积分别为0.83、0.86和0.94。结果表明，与ApEn和SampEn相比，DistEn无疑作为一种分类特征表现出始终如一的高性能。因此，DistEn作为从短长度RR间期数据中检测心律失常的生物标志物显示出有前景的表现。
