Design of a web laboratory interface for ECG signal analysis using MATLAB builder NE

Author:

Jaber Hussain A.12ORCID,Aljobouri Hadeel K.3,Çankaya Ilyas4

Affiliation:

1. National MR Research Center (UMRAM), Bilkent University , 06800 Ankara , Turkey

2. Department of Engineering of Medical Instrumentation Techniques, Kut University College , Kut , Iraq

3. Biomedical Engineering Department, College of Engineering, Al-Nahrain University , Baghdad 10072 , Iraq

4. Electrical and Electronics Engineering Department, Graduate School of Natural Science, Ankara Yıldırım Beyazıt University , 06010 Ankara , Turkey

Abstract

Abstract An electrocardiogram (ECG) is a noninvasive test, determining any defect in the heart rate or rhythm or changes in the shape of the QRS complex is very significant to detect cardiac arrhythmia. In this study, novel web-ECG simulation tools were proposed using MATLAB Builder NE with WebFigure and ASP.NET platform. The proposed web-ECG simulation tools consisted of two components. First, involved the analyses of normal real ECG signals by calculating the P, Q, R, S, and T values and detecting heart rate, while the second part related to extracting the futures of several types of abnormality real ECG. For calculating the PQRST values, simple and new mathematical equations are proposed in the current study using MATLAB. The Web ECG is capable to plot normal ECG signals and five arrhythmia cases, so the users are able to calculate PQRST easily using the proposed simple method. ECG simulation tools have been tested for validity and educational contributions with 62 undergraduate and graduate students at the Al-Nahrain University-Biomedical Engineering Department, Iraq. The proposed ECG simulation tools have been designed for academic learning to be run easily by a student using only any web browsers without the need for installing MATLAB or any extra programs. The proposed tools could provide a laboratory course for ECG signal analysis using a few buttons, as well as increase and develop the educational skills of students and researchers.

Publisher

Walter de Gruyter GmbH

Subject

General Computer Science

Reference32 articles.

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2. H. K. Aljobouri and F. E. Ali. “Brain-Computer interface based on VEP and FMRI package,” Am. J. Biomed. Sci., vol. 2019, no. 1. pp. 36–43, 2019. 10.5099/aj190100036.

3. N. Kumar, I. Ahmad, and D. P. Rai. “Signal processing of ECG using matlab.” 2012. Accessed: Apr. 07, 2019. [Online]. https://www.semanticscholar.org/paper/Signal-Processing-of-ECG-Using-Matlab-Kumar-Ahmad/750aa9af65c578a1f02450b20214fb0b849569e1.

4. H. K. Al-Jobouri. “Wireless bioinstruments for telecare,” 2011 1st Middle East Conference on Biomedical Engineering, MECBME 2011, 2011, pp. 5–10. 10.1109/MECBME.2011.5752052.

5. S. Karpagachelvi, M. Arthanari, and M. Sivakumar. “ECG feature extraction techniques – a survey approach,” May 2010, Accessed: Apr. 07, 2019. [Online]. http://arxiv.org/abs/1005.0957.

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