AI-Powered ECG Analysis for Early Detection of Hypertrophic Cardiomyopathy (HCM)

Imagine a world where your heartbeat can reveal silent killers before they strike. This project brings that future closer.

Hypertrophic Cardiomyopathy (HCM) is one of the most complex and life-threatening cardiovascular diseases, often hidden in plain sight. Traditional ECG analysis struggles to differentiate subtle abnormalities, leading to late diagnoses.

With this cutting-edge system, powered by ECG sensors + Machine Learning, the project transforms raw electrical heart signals into actionable intelligence. The ML model learns to identify the minute waveform patterns that escape the human eye, distinguishing between normal heart rhythms and those indicative of HCM.

🔹 Key Highlights

• ECG Signal Acquisition: Non-invasive measurement of real-time heart activity.

• Advanced Preprocessing: Noise filtering, feature extraction (QRS complex, ST-segment, P-wave analysis).

• Machine Learning Classifier: Deep Neural Network trained to detect the hallmarks of HCM.

• Clinical-Grade Output: Provides risk scores, early warnings, and diagnostic suggestions.

• Applications:

  • Smart wearable health monitors

  • Hospital diagnostic tools

  • Athlete screening for hidden heart diseases

  • Remote patient monitoring systems

This isn’t just a project—it’s a life-saving innovation, merging biomedical signals with artificial intelligence to unlock the hidden language of the heart.

Perfect for academic excellence, real-world healthcare impact, and portfolio value, this project gives you the power to create next-generation intelligent diagnostic systems.

✅ Deliverables:

• Full hardware + software kit

• 150-page research report

• Complete codebase with Google Colab ML model training

• Ready-to-run demo system