CARDIOBLINK - A Secure Web-Based Platform for ECG Analysis and Cardiac Disease Detection

This paper introduces the CARDIOLINK — a safe online foundation for convenient ECG analysis and heart diseases diagnosis. Security of access is the prime concern in this system hence only administrators are allowed to login. When an admin logs in, they are directed to a page which permits them to upload files that contain ECG data. The formats acceptable on this site include three; .dat file (data file), .hea file (header file) and .atr file (attribute file). Once the upload is done, it verifies if the uploaded files have been corrupted or not before giving feedback. Users can make this analysis start by pressing "Analyze" button after uploading the files. CARDIOLINK then displays two sets of patient’s ECG waveforms captured at different time intervals for comparison purposes to analyze them comparatively with each other. Upon reviewing both electrocardiograms, potential heart diseases suffered by a patient are indicated on results page viewable by user. Also, platform provides other details such as common symptoms; names of recommended drugs; factors of risks attached to identified disease and preventive measures. According to the research, done up to now, random forest algorithm is used beneath for the sake of disease foretelling because it robustly survives noise and gives high accuracy rate on large dataset like those produced by electrocardiogram machine.

Authors

Institutions

Publication Details

Published
2024-08-08
DOI
https://doi.org/10.1109/iccpct61902.2024.10672738
Primary Topic
ECG Monitoring and Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

CARDIOBLINK - A Secure Web-Based Platform for ECG Analysis and Cardiac Disease Detection

J Anudev, S Abhijith, Varun Krishna Jyothis, Hari Sankar S et al.
ECG Monitoring and Analysis
article

CARDIOBLINK - A Secure Web-Based Platform for ECG Analysis and Cardiac Disease Detection

J Anudev, S Abhijith, Varun Krishna Jyothis, Hari Sankar S, G. Lakshmi Vara Prasad
article en

Abstract

This paper introduces the CARDIOLINK — a safe online foundation for convenient ECG analysis and heart diseases diagnosis. Security of access is the prime concern in this system hence only administrators are allowed to login. When an admin logs in, they are directed to a page which permits them to upload files that contain ECG data. The formats acceptable on this site include three; .dat file (data file), .hea file (header file) and .atr file (attribute file). Once the upload is done, it verifies if the uploaded files have been corrupted or not before giving feedback. Users can make this analysis start by pressing "Analyze" button after uploading the files. CARDIOLINK then displays two sets of patient’s ECG waveforms captured at different time intervals for comparison purposes to analyze them comparatively with each other. Upon reviewing both electrocardiograms, potential heart diseases suffered by a patient are indicated on results page viewable by user. Also, platform provides other details such as common symptoms; names of recommended drugs; factors of risks attached to identified disease and preventive measures. According to the research, done up to now, random forest algorithm is used beneath for the sake of disease foretelling because it robustly survives noise and gives high accuracy rate on large dataset like those produced by electrocardiogram machine.

Vol. 7
Amrita Vishwa Vidyapeetham (IN)
Openalex Percentile: Top 71%
ECG Monitoring and Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.