Open Access Journal

ISSN : 2395-2717 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Electrical and Electronic Engineering(IJEREEE)

Monthly Journal for Electrical and Electronic Engineering

ISSN : 2395-2717 (Online)

Call For Paper : Vol 11, Issue 05, May 2024
Lab VIEW Based Heart Disease Detection

Author : Jasmin John Joseph 1 Jeril Benny 2 Jerrine George Zachariah 3 Jibin Mathew Valiyaveettil 4 Mathew George 5

Date of Publication :7th April 2016

Abstract: Electrocardiogram (ECG) signal shows the electrical activity of the heart and provides useful information that helps in analyzing the patient’s heart condition. This paper gives an insight in to the LabVIEW software which helps in the analysis of ECG signals. LabVIEW (Laboratory Virtual Instrument Engineering Workbench) is a graphical programming language that uses icons instead of lines of text to create programs. Processing of an ECG signal is done in two stages, filtering & feature extraction. Filtering is done through wavelet transform technique to remove the baseline wandering and noise due to breathing. ECG feature extraction VI is used for extracting various features like P onset, P offset, QRS onset, QRS offset, T onset, T offset, R, P & T wave, with which we calculate various parameters like Heart rate, QRS amplitude and their time duration. Further the heart rate is used to detect tachycardia and bradycardia conditions, while QT mean values are used to diagnose various heart diseases such as atrial tachycardia and hyperkalemia. The obtained result is alerted to the doctor through wireless communication.

Reference :

    1. Poonam Kaur, Prof. R. K. Sharma “LabVIEW Based Design of Heart Disease Detection System” IEEE International Conference on Recent Advances and Innovations in Engineering, May 2014
    2. Channappa Bhyri, Kalpana.V, S.T.Hamde, and L.M.Waghmare, “Estimation of ECG Features using LabVIEW” International Journal of Computing Science and Communication Technologies, VOL. 2, July 2009
    3. Y. W Feng Liu, Yutai Wang, “Research and Implementation of Heart Sound Denoising” International Conference on Solid State Devices and Materials Science, Elsevier 2012
    4.  Isha V Upganlawar, Harshal Chowhan, “Pre-processing of ECG Signals Using Filters” International Journal of Computer Trends and Technology (IJCTT) – volume 11 number 4 – May 2014
    5. Sani Saminu, Nalan Özkurt and Ibrahim Abdullahi Karaye, “Wavelet Feature Extraction for ECG Beat Classification” IEEE, 2014
    6. M. K. Islam, A. N. M. M. Haque, G. Tangim, T. Ahammad, and M. R. H. Khondokar, “Study and Analysis of ECG Signal Using MATLAB & LABVIEW as Effective Tools” International Journal of Computer and Electrical Engineering, Vol. 4, No. 3, June 2012

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