使用基于短时间和长时间RR间隔系列的交叉样本度测量心律失常的检测
Kanchan Sharma1, Ramesh Kumar Sunkaria1
1Department of Electronics and Communication Engineering Dr B R Ambedkar National Institute of Technology Jalandhar Punjab India.
Journal of arrhythmia
|June 16, 2023
概括
一种新的非线性技术,交叉样本 (CrossSampEn),通过使用心电图 (ECG) R-R间隔序列来改善心律失常的检测. 对于检测心房动 (AF) 和充血性心力衰竭 (CHF),CrossSampEn比样本 (SampEn) 更一致.
科学领域:
- 生物医学信号处理
- 心血管健康 心血管健康
- 非线性动力学是一种非线性动力学.
背景情况:
- 准确检测心律不整,如心房动 (AF) 和充血性心力衰竭 (CHF),仍然是生物医学信号处理的一个挑战.
- 电心电图 (ECG) 信号分析,采用线性和非线性测量,对于应对这些挑战至关重要.
研究的目的:
- 引入和评估一种新的非线性技术,交叉样本 (CrossSampEn),用于通过两系列分析量化健康状况.
- 为了比较CrossSampEn的有效性和一致性与已建立的单一系列样本 (SampEn) 方法用于检测心律失常.
主要方法:
- 该研究使用了来自正常鼻节律,AF和CHF的受试者的ECG记录.
- 应用交叉样本 (CrossSampEn) 来分析不同数据长度的相同和不同的R-R间隔序列的不规则性.
- 拟议的算法使用模拟数据和统计分析 (单向ANOVA) 进行了验证.
主要成果:
- 与SampEn相比,CrossSampEn表现出更高的一致性,特别是避免对短数据长度的未定义值.
- 统计验证 (单向ANOVA) 证实了算法的意义,具有很大的F值和p < .0001.1.
- 该方法有效量化了相同和不同的R-R间隔系列中的不规则性.
结论:
- 最佳的健康状况检测需要不同的RR间隔系列~1500个数据点和相同的RR间隔系列~1000个数据点,嵌入尺寸M=2和值r=0.2.2.
- 与样本相比,CrossSampEn提供了一种更一致,更可靠的测量方法来检测心律失常.
- 这些发现支持CrossSampEn作为生物医学信号处理中的一个有价值的工具,用于评估心血管健康.
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