EDA: Exploring PhysioNet’s Arrhythmia

Welcome to the Cardiovascular Health Insights project! This project focuses on the preprocessing of electrocardiogram (ECG) signals and utilizes Principal Component Analysis (PCA) for dimensionality reduction. By refining and reducing the dimensionality of ECG data, we aim to unlock profound insights into cardiac health, paving the way for advancements in cardiovascular healthcare.

Data Preprocessing and Dimensionality Reduction

In the third chapter of our series, we delve into crucial preprocessing techniques for ECG signals and the application of Principal Component Analysis (PCA) for dimensionality reduction. Here's an overview of what this project covers:

• Navigating the Challenges of Noise in ECG Signals: Importance of Preprocessing Discusses the impact of noise on ECG signals and the necessity of preprocessing techniques to enhance signal quality and accuracy.
• Preprocessing ECG Signals: Noise Removal Details various filtering techniques such as low-pass, high-pass, and band-pass filters used to mitigate noise in ECG signals, with a focus on the Butterworth filter.
• Restoring Data Integrity: Addressing Irregularities in ECG Signals Explores methods like imputation to handle irregularities and missing values in ECG datasets, ensuring data integrity for reliable analysis.
• Unraveling Insights: Harnessing PCA for Dimension Reduction Introduces Principal Component Analysis (PCA) as a tool to reduce the dimensionality of ECG data while preserving essential information, facilitating more efficient analysis and interpretation.
• Implementing Incremental PCA for Efficient Processing Demonstrates the implementation of Incremental PCA to manage large ECG datasets in manageable chunks, overcoming computational challenges and enabling deeper data exploration.

Requirements

• Python 3.x
• Pandas
• Postgres Client
• WFDB
• Bioscopy

Getting Started

• Clone the Repository:

https://github.com/Muneeb1030/EDA-of-Physionets-ECG.git

• Install Dependencies:

pip install requirements.txt

Additional Resources

Explore the project in detail through my Medium blog series (medium.com/@m.muneeb.ur.rehman.2000), where I share insights, motivation, and in-depth explanations about the Project.