Capstone2020 - Predicting AMIs using Machine Learning

Developing wearable armband for collecting ECG and Pulse Oximetry data and using machine learning to predict risk scores of Acute Myocardial Infarction

Project in three parts:

1. Research into MIT-BIH and ECGView II datasets (comprehensive cardiovascular datasets)
2. Designing and testing industry standard PCB board housing sensors, processing, and communication units
3. Processed datasets above and ran classification algorithms (Naive Bayes, SVM, Logistic Regression, CNN, RNN, XGBoost) in Python with Keras

This project was completed in collaboration with Lujain Ibrahim, Kai-Wen Yang, and Professor Mohamad Eid