ElectroCardioGram (ECG) Analyzer

An interpretable AI model that highlights the abnormal segments of the ECG and predicts the following heart diseases:
  • Conduction Disorder
  • Cardiac Hypertrophy
  • Myocardial Infarction
  • ST/T Change
Principal investigators: Dr. Anubha Gupta and Dr. Manu Kumar Shetty (MBBS, MD)

Cite: Atul Anand, Tushar Kadian, Manu Kumar Shetty, and Anubha Gupta, "Explainable AI Decision Model for ECG Data of Cardiac Disorders," Under Review, Biomedical Signal Processing and Control, Elsevier, January 2022.

Please note: AI model's results need to be confirmed by a cardiologist, the report cannot be used for any type of interventions without a doctor's consent.

Drop CSV here or
Select One

* Sampling Frequency = [ Total Number of Samples / Time (In Seconds) ].

Sample Files ( 100Hz)

Instructions

  • Upload ECG Data file with the following specifications:

    • CSV file (Comma Separated) with only numerical values.
    • Data arranged as columns in the lead order:

      [ I , II , III , AVL , AVR , AVF , V1 , V2 , V3 , V4 , V5 , V6 ]

    • Atleast 10 seconds of ECG data.
  • Select and Upload Data File
  • Enter Sampling Rate and Click Predict

  • Wait 30-60 Seconds For The Results.

Webapp by Dikshant Sagar