chavdad23543/Heart_Rate_and_Arrhythmia_Detection

Heart Rate and Arrhythmia Detection from Wearable Sensors

This Streamlit application analyzes wearable ECG/PPG signal data to estimate heart rate and detect possible arrhythmia using a trained deep learning model.

Features

• —Upload wearable sensor CSV data
• —Use built-in demo signal
• —Estimate heart rate in BPM
• —Detect heartbeat peaks
• —Classify heartbeat segments using a trained 1D CNN model
• —Show normal and abnormal heartbeat results
• —Download prediction results as CSV

Model

The deployed model is a 1D Convolutional Neural Network trained for ECG heartbeat classification.

Classes

Required Files