ECG Dataset for Heart Condition Classification
Description
This ECG dataset comprises three distinct classes: normal, abnormal, and disease-specific cardiac signals. Collected from both healthy individuals and patients with heart conditions, the dataset provides labeled ECG recordings suitable for training machine learning models aimed at real-time health monitoring and cardiac disease prediction. Each class contains a balanced number of high-quality ECG images, offering a valuable resource for developing and evaluating AI-based diagnostic tools in healthcare.
Files
Steps to reproduce
This dataset contains ECG recordings collected using a custom IoT device equipped with an ECG sensor. The data was gathered directly from the human body via electrodes placed on the chest, capturing the electrical activity of the heart in real-time. The dataset is divided into three classes: Normal, Abnormal, and History of MI signals, representing a range of heart conditions.