基于变分模态分解的SCG信号独立心跳提取

Tilendra Choudhary, L. Sharma, M. Bhuyan
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引用次数: 8

摘要

本文提出了一种基于变分模态分解(VMD)的地震心动图(SCG)信号心跳提取框架。该方法不需要参考心电图等心脏信号。该方法包括四个主要步骤:利用VMD算法对信号进行分解、构建心率包络、对构建的包络进行低通滤波、对平滑包络进行标注。该方法用PZCI、NZCI、PI、TI等特征点对HR包络进行标注。每个特征点都可以用于SCG循环提取。所提出的方法在Physionet存档的CEBS数据库中进行了测试和验证。实验结果表明,采用峰值实例(peak instance, PI)的方法得到的结果一致,且精度较高。定性分析结果表明,该方法对健康受试者具有良好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Standalone Heartbeat Extraction in SCG Signal Using Variational Mode Decomposition
In this paper, a variational mode decomposition (VMD) based heartbeat extraction framework is proposed for seismocardiogram (SCG) signal. A reference cardiac signal such as ECG is not needed in our proposed method. The proposed method consists of four major steps: signal decomposition using VMD algorithm, heart rate (HR) envelope construction, low pass filtering of constructed envelope, and annotation of smoothed envelope. The method annotates the HR envelope in terms of characteristic points such as PZCI, NZCI, PI, and TI. Each of the characteristic points can be used for SCG cycle extraction. The proposed method is tested and validated with CEBS database available at the Physionet archieve. Based on the experimental results, it is observed that the proposed method with peak instances (PI) achieves consistent results with good accuracy among all. The qualitative analysis of performance results shows good performance of the proposed method for healthy subjects.
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