Heart Rate Anomaly Detection
An ECG monitoring and anomaly detection system for the card10 badge. Collects heart rate data via Bluetooth, streams it to a Python dashboard for real-time visualization and anomaly detection.
About This Project
I built this project to explore real-time health data processing with the card10 badge. The system uses the card10 badge from the 2019 Chaos Communication Camp, equipped with a MAX30001 ECG sensor running MicroPython, which streams heart rate data over Bluetooth Low Energy to a Python backend.
The data flows into a Streamlit dashboard where you can watch heart rate patterns in real time. Behind the visualization, an Isolation Forest algorithm from scikit-learn continuously analyzes the signal for anomalies—irregular heartbeats, sudden spikes, or drops that might indicate a problem.
The full pipeline covers hardware (MicroPython on the card10 badge), wireless communication (BLE via bleak), signal processing (scipy), data handling (pandas, numpy), machine learning (scikit-learn), and interactive visualization (Streamlit, plotly). It’s a compact example of end-to-end IoT data collection, processing, and alerting.