Prisha Marpu

How can machine learning techniques be used to analyze electrocardiogram (ECG) signals to understand and accurately detect cardiac arrhythmia?

Started Nov. 21, 2023

Abstract or project description

This research project focuses on using machine learning to better understand and accurately detect irregular heartbeats, known as cardiac arrhythmia, from electrocardiogram (ECG) signals. Detecting and addressing these irregularities early is crucial for effective treatment. The project aims to create a system that can analyze ECG data, picking up on subtle patterns that indicate different types of arrhythmias.

To ensure the system is reliable and applicable, I will gather a diverse set of ECG recordings that cover different demographics and cardiac conditions. The data will go through a cleanup process to remove any unnecessary details or interference, making sure the machine learning algorithms get the best quality input. I will explore various machine learning models to pull out important information from the data. The models are still to be decided.

Once I developed these models, I will train and test them using datasets that have been labeled for accuracy. I will measure how well the models perform by comparing it to the actual results.

The goal of this project is to create a machine learning system that can give early and accurate insights into cardiac arrhythmia. This allows for people to have some buffer time before their medical conditions get worse.