ECG Paper Digitization and R Peaks Detection Using FFT

Author:

Fathail Ibraheam1ORCID,Bhagile Vaishali D.2ORCID

Affiliation:

1. Faculty of Computer Sciences & IT, Hajjah University, Hajjah, Yemen

2. Department of Computer Science and IT, Animation Deogiri College, Aurangabad Affiliated to Dr. B.A.M.U, Aurangabad, India

Abstract

An electrocardiogram (ECG) uses electrodes to monitor the heart rhythm and identify minute electrical changes that occur with each beat. It is employed to investigate particular varieties of aberrant heart activity, such as arrhythmias and conduction problems. One of the most essential tools for detecting heart problems is the electrocardiogram (ECG). The majority of ECG records are still on paper. Manual ECG paper record analysis can be difficult and time-consuming. It is possible to digitally digitize these paper ECG recordings for automated analysis and diagnosis. In this paper, we proposed a system to digitize the ECG paper, automatically detecting R peaks, calculating the average heart rate, and sending SMS to the doctor via cloud in the event of detection of abnormality. The method of the system is uploading an ECG image, then dimensionality reduction, feature extraction in the form of digital signals, and saving it in a CSV file format using the MATLAB programming language. After that, the system retrieves the signals for further processing of the raw signals. We used the fast Fourier transform (FFT) algorithm to calculate R peaks and calculate the heart rate. If the heart rate is abnormal, the system sends SMS messages to doctors via a technology platform (Twilio) using the Python programming language.

Publisher

Hindawi Limited

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Civil and Structural Engineering,Computational Mechanics

Cited by 4 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

1. Comparing Tree-Based Ensemble Machine Learning Models and Convolutional Neural Network for Automatic Classification of Heart Abnormalities from ECG Images;2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT);2023-07-06

2. Advanced ICU Patient Monitoring With Sensor Integration, IV Detection WITH Canny Edge Detection and ECG Monitoring With Live Feed;2023 International Conference on Recent Advances in Electrical, Electronics & Digital Healthcare Technologies (REEDCON);2023-05-01

3. A Deep Learning Architecture Using 3D Vectorcardiogram to Detect R-Peaks in ECG with Enhanced Precision;Sensors;2023-02-18

4. Automated Defective ECG Signal Detection using MATLAB Applications;2022 IEEE International Conference on Current Development in Engineering and Technology (CCET);2022-12-23

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