从心电图信号中精确检测和定位R峰值
Diguo Zhai1,2, Xinqi Bao3, Xi Long4
1Guangdong Provincial Key Laboratory of Optical Information Materials and Technology, Institute of Electronic Paper Displays, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, China.
Mathematical biosciences and engineering : MBE
|December 5, 2023
概括
一个新的算法精确地定位了心电图 (ECG) 信号中的R峰值,改善了心率变化 (HRV) 分析. 这种增强的R峰检测比传统方法更准确.
科学领域:
- 生物医学工程 生物医学工程
- 信号处理 信号处理
- 心脏病学 心脏病学
背景情况:
- 心率变化 (HRV) 分析依赖于从心电图 (ECG) 信号中准确检测R峰值.
- 现有的R峰检测算法往往优先考虑灵敏度而不是精确的R峰定位,从而限制了HRV分析的准确性.
- 对于改进的临床应用,需要算法能够精确地确定R峰位置.
研究的目的:
- 引入一种具有增强精度的新型R峰本地化算法.
- 改进广泛使用的Pan-Tompkins (PT) 算法用于R峰检测.
- 评估算法在ECG信号中准确定位R峰的性能.
主要方法:
- 修改了Pan-Tompkins算法用于R峰检测.
- 应用带通波 (5-35 Hz) 和信号方程来增强QRS复合体.
- 使用具有200ms的最小宽度的动态值来定义QRS复杂窗口.
- 实现的模板与自动生成的QRS模板匹配,用于精确的R峰识别.
主要成果:
- 在MIT-BIH心律失常数据库中实现了高性能指标:99.78%的灵敏度 (SE),99.78%的正预测值 (PPV) 和0.44%的数据错误率 (DER).
- 显著减少了8.35毫秒的注释检测误差 (ADE),表明了精确的R峰定位.
- 超过了经典的Pan-Tompkins算法,该算法报告SE为98.87%,PPV为99.14%,DER为1.98%和ADE为21.65 ms.
结论:
- 拟议的算法精确地检测了ECG信号中的R峰位置.
- 这种高精度的R峰定位有可能增强HRV分析的临床应用.
- 该算法比现有的ECG信号处理方法提供了有价值的改进.
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