Bioband Display - Continuous Health Monitoring

Bioband Display is an Android application designed to connect to and visualize real-time data from a custom nRF52840-based bio-sensing device. It serves as the mobile interface for a complete continuous health monitoring system, handling Bluetooth LE communication, advanced Python-based data analysis, and multi-sensor graphical representation.

What It Does

The app scans for a specific bio-sensing device named Test Device, establishes a Bluetooth Low Energy (BLE) connection, and listens for multiplexed data notifications. Upon receiving data (EMG, PPG, Sweat, or Test/ECG), the app uses an integrated Python environment (via Chaquopy) to process it and displays the results as live, auto-scrolling line graphs.

This project demonstrates a full end-to-end medical data pipeline: from hardware sensors, through an embedded microcontroller and BLE, to a mobile application for real-time analysis, storage, and visualization.

Key Features

• Automatic BLE Connection: Scans for and connects to the nRF52840 device automatically.
• Multi-Sensor Support: Dedicated interfaces for:
  • EMG Data: Real-time muscle activity monitoring.
  • PPG Data: Heart rate and oxygen saturation monitoring.
  • Sweat Data: Conductive sensor analysis.
  • ECG/Test Data: Advanced plotting of multi-column data from sensors or CSV imports.
• On-Device Data Processing: Utilizes a Python backend (NumPy, Pandas, SciPy) integrated directly into the app to execute complex analysis logic translated from MATLAB.
• CSV Data Management:
  • Real-time Logging: Saves incoming EMG data to emg_data_log.csv in internal storage for later review.
  • Historical Graphing: Ability to load and visualize multi-column CSV files (e.g., Time, ECG, Blood Pressure) using MATLAB-style processing logic.
• Real-time Data Visualization: Smooth, high-performance rendering using the MPAndroidChart library.

How to Get Started

Prerequisites

1. Android Studio: Latest stable version.
2. Android Device: A physical phone running Android 7.0 (API 24) up to Android 15 (API 35).
3. Python for Build Machine: Local installation of Python 3.10 required for the Chaquopy build process.
4. Hardware: The custom nRF52840 "Bioband" device.

Setup and Installation

1. Clone the repository: git clone https://github.com/kristinscot/Continuous-Health-Monitoring-.git
2. Open in Android Studio: Select Open and navigate to the project folder.
3. Sync Project: Let Android Studio sync Gradle. This will install Python dependencies (numpy, pandas, scipy) automatically.
4. Run the App: Connect your phone and click the Run button.

Architecture

• Frontend: Kotlin (Activities), XML (Layouts), MPAndroidChart (Graphing).
• Backend Logic: Python 3.10 (via Chaquopy).
• Communication: BLE (Bluetooth Low Energy) using a custom Service/Characteristic protocol.
• Storage: Internal App Storage (CSV logging).

Who We Are

This project is part of a continuous health monitoring research initiative.

• Maintainer: Kristin