easyG

Making ECG analysis easier for doctors, Life better for patients.

Comment

Inspiration

In Singapore, 21 people die from cardiovascular disease (heart diseases and stroke) every day. Cardiovascular disease accounted for 32% of all deaths in 2021. This means that almost 1 out of 3 deaths in Singapore is due to heart diseases or stroke. But this is preventable with early detection and therefore early treatment which helps to reduces suffering, prevents complications such as heart failure, stroke and kidney disease.

ECG Specialist are the ones that analyze the ECG signals and give the results. However, results can take up to from 1 - 2 weeks to receive. This is a problem as time is essential for those might have cardiovascular diseases and we would want to get the results as soon as possible. How can AI help with this?

What it does

Thats why we built easyG. A custom built API that takes in raw ECG data and returns: 1) Filtered signal with less noise

2) Physiological Measurements such as:

  • Heart Rate
  • Breathing Rate
  • Interbeat Interval

3) Arrhythmia Classification Using a custom trained CNN model using Kaggle Dataset

Classify arrhythmia into 5 classes:

  • Non-ecotic beats (normal beat)
  • Supraventricular ectopic beats
  • Ventricular ectopic beats
  • Fusion Beats
  • Unknown Beats

Achieved 95.14% accuracy on test data

How we built it

AWS Services used: Lambda Cloud9 API Gateway S3 Cloudwatch

How to try it in Postman

Raw Data in Body: 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What's next for easyG

Integrate API with Web applications e.g. make our own web application or possible to integrate it with existing healthcare applications

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