Virtual instrument based real time ECG monitoring device

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...

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Bibliographic Details
Main Authors: Singh, O. P., Malarvili, M. P.
Format: Conference or Workshop Item
Language:English
Published: 2020
Subjects:
Online Access:http://eprints.utm.my/id/eprint/92943/1/MBMalarvili2020_VirtualInstrumentBasedRealTime.pdf
http://eprints.utm.my/id/eprint/92943/
http://dx.doi.org/10.1088/1757-899X/884/1/012011
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Summary: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.