一种基于GASF和MPRE2D的ECG特征提取方法,用于检测充血性心力衰竭
Juanjuan Yang1, Wenhui Wang2, Caiping Xi3
1Nanjing Institute of Rolling Stock Technology, Nanjing, 210000, Jiangsu, China. 211110302108@stu.just.edu.cn.
Physical and engineering sciences in medicine
|January 26, 2026
概括
这项研究引入了一种用于检测充血性心力衰竭 (CHF) 的新方法,该方法使用由格拉米安角总和场 (GASF) 生成的心电图 (ECG) 图像,并使用二维多尺度变换比 (MPRE2D) 分析. 该技术在从短时间的心电图记录中识别CHF时具有很高的准确性.
科学领域:
- 心脏病学 心脏病学
- 生物医学工程 生物医学工程
- 信号处理 信号处理
背景情况:
- 充血性心力衰竭 (CHF) 是一种重要的心血管疾病.
- 电心电图 (ECG) 信号对于诊断诸如心脏不全等心脏病至关重要.
- 在CHF检测的挑战包括低幅度和短时间的心电图信号.
研究的目的:
- 开发一种使用ECG信号检测CHF的有效方法.
- 为了解决CHF检测传统心电图分析的局限性.
- 为了提高CHF诊断的准确性和效率.
主要方法:
- 预处理心电图信号并使用格拉米安角总和场 (GASF) 算法将其转换为图像.
- 应用二维多尺度换比 (MPRE2D) 来量化心电图像的复杂性和不规则性.
- 提取MPRE2D特征并使用支持矢量机 (SVM) 进行分类.
主要成果:
- 实现了高分类准确度 (99.46%),灵敏度 (99.36%),特异性 (99.63%),以及F1评分 (99.56%) 的CHF检测.
- 使用仅2秒的心电图信号长度证明有效的CHF检测.
- 在正常鼻节律和CHF数据库上验证了该方法.
结论:
- 拟议的基于GASF和MPRE2D的方法为CHF检测提供了一种有效的方法.
- 这种技术为临床评估和治疗心血管疾病提供了宝贵的见解.
- 这些发现对CHF风险评估具有重大临床影响.
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