Why ECG Viewer

ECGs have not changed in the way they are presented over more than a century. Often they are still printed on paper. When presented in the digital form, this is still as an image or pdf replicating the printed ECG. In today's computer age, we should be able to better utilise the ECG recorded in a digital form. Different formats used to store digital ECGs was a stumbling block to this approach. This has been mostly sorted out with the use of the XML format as a standard for digital ECGs. XML is a document format designed to display information in a manner that is both human readable and machine readable (1). Most ECG machines now provide the capability to store and export recorded ECGs in a standard XML format. However, viewers for displaying and manipulating ECGs recorded in the XML format are not widely available. This app was created to see ECGs recorded in this format. Since the electrical information recorded is available as raw data, it is easy to change the way this is displayed. Simple examples are changing the ECG display speed, amplitude calibration or the lead used as the rhythm lead. But the possible customizations are really unlimited. This viewer is also used as a testing ground for different visualizations of the ECG.

  1. https://en.wikipedia.org/wiki/XML

How to display an ECG here

To quickly check out the ECG viewer, you can see the sample ECGs listed on the homepage. There is also a library which is constantly being updated with ECGs recorded in patients with various cardiac conditions. The ECGs in this library can also be seen with the viewer. You can also see ECGs recorded by you with the viewer. For this you will need to record the ECGs in the XML format. The exact steps will vary with the recorder used, but in general, this involves setting XML as the export format, then recording an ECG and exporting it to an external storage connected through USB or to another computer over a network.

Additional leads

Right sided and posterior leads are derived using coefficients from a published paper (1). Elevated leads are based on work from our team that is not yet published.

  1. http://dx.doi.org/10.22489/CinC.2020.208

How and why do I correct QRS detection

For displaying a single beat, QRS complexes are detected automatically and an average beat is created. An unsophisticated detection method is used which can fail sometimes with for example, false detection of T waves also as QRS complexes. Such false detection will result in the single beat not looking right. The QRS detection is displayed in a small panel and this can be used to check if the detection is accurate. QRS complexes will be marked with a green circle while complexes detected as QRS, but which are ectopics and therefore not used for creating the averaged beat will be marked with a red cross. If the detection is not right, change the lead used for detection using the dropdown. Choosing a lead with prominent QRS complexes and less prominent T waves will provide better results. The result of changing the lead can be reflected immediately and can be verified.


The ECGs you upload are stored on the server. Since some server side processing is involved, this is a necessary step. Any patient data entered during the ECG recording is stored in the XML file and displayed when viewing the ECG. Uploaded ECGs are routinely cleared after a certain period, around 24 hours usually.

About the ECG library

The ECG library is a collection of ECGs recorded in the XML format in patients with different cardiac conditions. All identifying information has been removed from the ECGs. These are expected to be helpful to those learning about ECG abnormalities in different conditions. These also serve to test and develop this viewer. The ECGs have been collected by the residents of the Department of Cardiology at JIPMER, especially by Dr. Chinmay and Dr. Ramanathan.

Future Plans

  • Improved display of vectorcardiograms
  • 'Ring' display of waveforms for easier understanding of axis and changes in amplitude
  • Make available derived right precordial leads
  • Superimpose a second ECG over the displayed ECG for comparison
  • Better automatic waveform boundary detection
  • User accounts with ability to store ECGs for long term
  • Assisted QT interval measurement by showing tangents

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