Parallel Distributed Framework for State Space Adaptive Filter for Removal of PLI from Cardiac Signals

Q4 Agricultural and Biological Sciences International Journal Bioautomation Pub Date : 2021-09-01 DOI:10.7546/ijba.2021.25.3.000781
I. Rehman, H. Raza, N. Razzaq
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引用次数: 2

Abstract

Cardiac signals are often corrupted by artefacts like power line interference (PLI) which may mislead the cardiologists to correctly diagnose the critical cardiac diseases. The cardiac signals like high resolution electrocardiogram (HRECG), ultra-high frequency ECG (UHF-ECG) and intracardiac electrograms are the specialized techniques in which higher frequency component of interest up to 1 KHz are observed. Therefore, a state space recursive least square (SSRLS) adaptive algorithm is applied for the removal of PLI and its harmonics. The SSRLS algorithm is an effective approach which extracts the desired cardiac signals from the observed signal without any need of reference signal. However, SSRLS is inherited computational heavy algorithm; therefore, filtration of increased number of PLI harmonics bestow an adverse impact on the execution time of the algorithm. In this paper, a parallel distributed SSRLS (PD-SSRLS) algorithm is introduced which runs the computationally expensive SSRLS adaptive algorithm parallely. The proposed architecture efficiently removes the PLI along with its harmonics even the time alignment among the contributing nodes is not the same. Furthermore, the proposed PD-SSRLS scheme provides less computational cost as compared to sequentially operated SSRLS algorithm. A comparison has been drawn between the proposed PD-SSRLS algorithm and sequentially operated SSRLS algorithm in term of qualitative and quantitative performances. The simulation results show that the proposed PD-SSRLS architecture provides almost same qualitative and quantitative performances than that of sequentially operated SSRLS algorithm with less computational cost.
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用于去除心脏信号PLI的状态空间自适应滤波器的并行分布式框架
心脏信号经常被伪影破坏,如电力线干扰(PLI),这可能会误导心脏病专家正确诊断关键心脏疾病。高分辨率心电图(HRECG)、超高频心电图(UHF-ECG)和心内电图等心脏信号是观察高达1KHz的感兴趣高频分量的专业技术。因此,采用状态空间递归最小二乘(SSLLS)自适应算法来去除PLI及其谐波。SSLLS算法是一种从观测信号中提取所需心脏信号而不需要参考信号的有效方法。然而,SSLLS是一种继承的计算量大的算法;因此,PLI谐波数量增加的滤波对算法的执行时间产生不利影响。本文介绍了一种并行分布式SSLS(PD-SRLS)算法,该算法并行运行计算量大的SSLS自适应算法。所提出的架构有效地去除了PLI及其谐波,即使贡献节点之间的时间对准不相同。此外,与顺序操作的SSLLS算法相比,所提出的PD-SRLS方案提供了更少的计算成本。在定性和定量性能方面,将所提出的PD-SRLS算法与顺序操作的SSLLS算法进行了比较。仿真结果表明,所提出的PD-SRLS结构提供了与顺序操作的SSLLS算法几乎相同的定性和定量性能,并且计算成本较低。
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来源期刊
International Journal Bioautomation
International Journal Bioautomation Agricultural and Biological Sciences-Food Science
CiteScore
1.10
自引率
0.00%
发文量
22
审稿时长
12 weeks
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