Virtual Instrument Based Real Time ECG Monitoring Device

Author:

Singh Om Prakash,Malarvili MB

Abstract

Abstract This study presents a real-time ECG monitoring system based on a virtual instrument. The device was designed using surface electrode, lead wire, instrumentation amplifier (IN114), and passive low pass filter with cut-off frequency (fc, 180 Hz). Thereafter, the ECG signal was transferred via DAQ card by initializing the analog input and sampling rate to the Labview for further analysis. Further, digital notch filter (fc, 47 to 53 Hz), bandpass filter (fc, 0.05 to 20 Hz), and FIR high pass filter using Kaiser window (order-56, and fc – 3.5 Hz) was employed in order to remove the power line interference, detect fiducial point from ECG, and eliminate the baseline wondering. In addition, we examined the various wavelet to choose the best to use wavelet denoise based on signal-to-noise ratio (SNR). Finding suggests the SNR (58.75 dB) of sym8 wavelet was higher comparing with another wavelet. Hence, the wavelet denoising was implemented into the developed device to remove the distortion and to detect the better peak in real time. Further, multiresolution analysis with Haar wavelet with the decomposing level of 1 was incorporated into the developed ECG monitoring device to detect the R-R peak, followed by automatic heart rate detection. Thus, this finding suggests the promising result that has the potential to assess the cardiovascular conditions. In future, the developed device will be tested with healthy subjects in order to standardize the functionality and significant features will be extracted from the morphology of ECG waveform for the analysis of cardiovascular diseases.

Publisher

IOP Publishing

Subject

General Medicine

Reference25 articles.

1. Heart disease and stroke statistics- 2014 update: a report from the American Heart Association;Go;Circulation,2013

2. Fast multi-scale feature fusion for ECG heartbeat classification;Ai;EURASIP J. Advances in Signal Processing,2015

3. World health statistics - part 6: SDG health and health- related targets,2016

4. QRS detection based on wavelet coefficients;Zidelmal;Comp. Meth. Prog. Biomed.,2012

5. Envelopment filter and K-means for the detection of QRS waveforms in electrocardiogram;Merino;Med. Eng. Phys.,2015

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3