Documented case
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Case type
Healthtech, BLE, and biomedical signal work
Surface
Public repository
Technical focus
Flutter · Dart · Bluetooth/BLE
Proof
Public repositories for the app and BLE monitor, plus a real system screenshot.
Healthtech, BLE, and biomedical signal work
AWECG Monitoring System
Healthtech case combining Flutter, Bluetooth/BLE, applied electronics, and TensorFlow Lite for real-time ECG monitoring on custom hardware.
Flutter
Dart
Bluetooth/BLE
TensorFlow Lite
ESP32
AD8232
Windows
Android
Problem
As an Electronic Engineering degree project, the challenge was not only to visualize a signal. It required covering the full flow: acquisition from dedicated hardware, stable BLE transmission, real-time monitoring, meaningful signal reading, and automated support for arrhythmia classification.
Solution
AWECG was developed as an end-to-end system: a Flutter app for Windows and Android, real-time visualization with dynamic scaling, secure local storage, PDF report generation, and a TensorFlow Lite model for signal classification. The system connects to a custom ESP32 + AD8232 monitor over BLE.
Responsibilities
Cross-platform Flutter architecture, Bluetooth/BLE integration, biomedical signal visualization, large-volume data handling, TensorFlow Lite integration, clinical reporting, and app-hardware connectivity.
Results
The project was documented and published on GitHub as both a public application and a separate BLE monitor, demonstrating real capability in Flutter, applied electronics, BLE, and signal processing within a healthtech context.
image
Real AWECG screenshot showing real-time ECG monitoring from Flutter.
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