Final Year Project for my B.Tech in 2022.
If you're copying stuff just cite the project - it won't hurt your GPA!
Project-HEART is an automated and portable heart disease analyzer that integrates hardware and software for real-time ECG monitoring and arrhythmia analysis. The system uses an ESP8266 (or any WiFi-enabled Arduino) connected to an AD8232 ECG sensor to capture heart signals. Users can view their ECG graph in real time and analyze the data using a deep neural network (DNN) model (TensorFlow Lite) within the Android app.
- Hardware Integration: Connects to ESP8266/Arduino devices with AD8232 ECG sensors over WiFi.
- Android Application: Visualizes ECG signals and provides arrhythmia classification using an on-device TensorFlow Lite model.
- Machine Learning: Uses a DNN trained on the Kaggle ECG dataset to analyze heartbeats for arrhythmia detection.
- Portable and Automated: Designed for easy deployment and use in various environments.
- ESP8266 or any WiFi-enabled Arduino board
- AD8232 ECG Sensor
- (Optional) SSD1306 OLED display
- Android Studio (for compiling the app)
- Arduino IDE (for flashing the microcontroller)
- Outdated library dependencies may require code modifications for compatibility.
- Kaggle ECG dataset (used for training the machine learning model)
- Set up the hardware (ESP8266/Arduino + AD8232 sensor) and upload the firmware.
- Install and run the Android app.
- Connect the app to the device over WiFi.
- Visualize ECG signals in real time.
- Use the built-in analysis tool to classify heartbeats and detect arrhythmias.
Note: This project code is outdated and may not work with the latest libraries without modifications.
This project is licensed under the Apache 2.0 License.