Estimation of Respiratory Rate from the ECG Using Instantaneous Frequency Tracking FxLMS Algorithm

Shephali Gupta, J. B. Sharma
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引用次数: 1

Abstract

Respiratory rate (RR) monitoring is very important in the hospitality environment and is used to measure various diseases. In this paper an adaptive algorithm to find respiration rate using modified weighted multi signal oscillator based filtered least mean square (W-OSC-FxLMS) algorithm is presented. In this method RR is determined from single lead electrocardiogram (ECG) by tracking the instantaneous frequency in respiratory sinus arrhythmia (RSA) and respiratory peak amplitude (RPA) waveforms. In this work adaptive approach is applied with W-OSC algorithm based multi signal frequency tracking to find RR. Adaptive filtered least mean square (FxLMS) algorithm combined with weighted multi signal oscillator based (W-OSC) algorithm improves the tracking accuracy. Simulation are performed on physionet fantasia dataset shows that the proposed algorithm out performs the conventional methods. Proposed method is also having the advantages such as less bulky, inexpensive can be used in peacemaker and body area network applications.
基于瞬时频率跟踪FxLMS算法的心电呼吸频率估计
呼吸频率(RR)监测在酒店环境中非常重要,用于测量各种疾病。本文提出了一种基于改进加权多信号振荡器滤波最小均方(W-OSC-FxLMS)算法的呼吸速率自适应算法。该方法通过跟踪呼吸性窦性心律失常(RSA)和呼吸峰幅(RPA)波形的瞬时频率,从单导联心电图(ECG)中确定RR。本文将自适应方法与基于W-OSC算法的多信号频率跟踪相结合来寻找RR。自适应滤波最小均方(FxLMS)算法与基于加权多信号振荡器(W-OSC)算法相结合,提高了跟踪精度。在physionet fantasia数据集上进行了仿真,结果表明该算法优于传统方法。所提出的方法还具有体积小、价格低廉等优点,可用于维和和体域网络应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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