REAL TIME WIRELESS ECG SIGNAL-BASED HEART DISEASE PREDICTION SYSTEM USING HVD

Authors:

Raja Krishnamoorthy,Siva Shankar. S,Pogu Vignan,

DOI NO:

https://doi.org/10.26782/jmcms.2020.03.00015

Keywords:

Electrocardiogram (ECG),Hilbert vibrating decomposition (HVD),Signal quality index (SQI),Universal serial bus (USB),Transistor transistor logic (TTL),

Abstract

In this paper, ECG signal-based heart prediction system using HVD is proposed for continuous cardiac health monitoring applications. This proposed work consists of four blocks 1)ECG signal sensing from human body 2) uploading ECG signal to MATLAB 3) ECG signal analysis 4) SQI and disease identification. Wireless ECG system  is built by using AD8232 module and HC-05, electrical activity is taken from it and transmit it wireless to the USB to TTL via HC-05 ,all the live signal is saved in the form of matfile. In  ECG signal analysis, raw signal is filtered by using HVD and it find RR intervals and QRS complex. In SQI it will check whether signal is good, or diagnosis based on RR interval and QRS complex. if the condition is diagnosis it goes for disease identification , if any disease is identified all the data in form matfile is sent as email to doctor. The main moto is to design electronic T-shirt for continuous cardiac health monitoring. This system has enough potential for assessing biomedical diagnosis system.

Refference:

I. A. Agrawal and D. H. Gawali, “Comparative Study of ECG Feature Extraction Methods”, 2ndIEEE International Conference On Recent Trends in Electronics Information and Communication Technology, May 19-20, 2017, India.

II. A.Sellamiet.al.,“ECG as a Biometric for Individual’s Identification”, The 5thInternational Conference on Electrical Engineering – Bombardes, 2014, October 29-31, Bombardes, Algeria.
III. B. Liu et al., ‘The Design of Portable ECG Health Monitoring System’, 29th Chinese Control And Decision Conference, 2017.

IV. B.Vuksanovic, A. Mustafa, “ECG Based System for Arrhythmia Detection and Patient Identification”, In: Int. Conf. on Information Technology Interfaces, Cavtat, Croatia, 2013.

V. J. Chai, “The Design of Mobile EEG Monitoring System”, IEEE 4thInternational Conference on Electronics Information and Emergency Communication, 2013.

VI. Jian-Zhi Chen et.al.,“Design of ECG Signal Acquisition System Based on ADS1291”, In International Conference On Communication Problem-Solving, 2016.

VII. K. Raja, et. al., “Design of a low power ECG signal processor for wearable health system-review and implementation issues”,In11thInternational Conference Intelligent Systems and Control, 2017, pp. 383-387. IEEE, 2017.

VIII. K. Raja,et. al., “Design of a spike detector for fully Integrated Neuromodulation SoC”, In 11thInternational Conference on Intelligent Systems and Control, 2017, pp. 341-345.

IX. R. N.Mitraet.al., “Pattern Classification of Time Plane Features of ECG Wave from Cell-Phone Photography for Machine Aided Cardiac Disease Diagnosis”, 36thAnnual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014.

X. S. Udit, B.Ramkumar and M. S.Manikandan, “Real-Time Signal Quality-Aware ECG Telemetry System for IoT-Based Health Care Monitoring”, IEEE Internet of Things Journal, Vol. 4, no. 3, pp:815-823, 2017.

XI. T. G. Keshavamurthy and M. N. Eshwarappa, “Review Paper on Denoising of ECG Signal”, In 2nd International Conference on Electrical, Computer and Communication Technologies, 2017.

XII. Tsair Kao et.al., “Computer Analysis of the Electrocardiograms from ECG Paper Recordings”, Proceedings of 23rdAnnual EMBS International Conference, 2001, October 25-28

XIII. W. Ahmed and S. Khalid, “ECG Signal Processing for Recognition of Cardiovascular Diseases: A Survey”, 6thInternational Conference on Innovative Computing Technology, 2016,pp:677-682.

XIV. Y. Miao et al., “Research and Implementation of ECG-Based Biological Recognition Parallelization”, Special Section on Key Technologies for Smart Factory of Industry 4.0, IEEE Access, Vol.6,pp:4759-4766, 2017.

View Download