UNOsense: DIY Healthcare Sensor

University of Cambridge 2021

Brief Description

UNOsense introduces an accessible, DIY solution for healthcare monitoring, providing real-time pulse and temperature data through a cost-effective and open-source design.

Utilising an Arduino microcontroller, Raspberry Pi, and Cloud integration, this project addresses the increasing demand for affordable healthcare solutions, particularly in resource-limited settings.

More information

With the ongoing pandemic highlighting the need for efficient healthcare monitoring, UNOsense offers a practical approach to vital signs tracking. By leveraging affordable components, this project demonstrates how DIY healthcare devices can enhance patient monitoring capabilities, especially in developing regions.

System Diagram

System Overview

The UNOsense system is composed of three primary components: the sensor node, Raspberry Pi, and the Cloud. The sensor node integrates temperature and pulse sensors connected to an Arduino, which processes and transmits data via a Raspberry Pi to a cloud-based server for storage and analysis.

Sensor Node

Sensor Node Details

The sensor node uses an LM35 temperature sensor and a photodiode-based pulse sensor. These sensors are interfaced with the Arduino using operational amplifiers to ensure accurate readings. An OLED display provides real-time feedback to the user.

LM35 Circuit

Temperature Sensor Calibration
The LM35 temperature sensor required precise calibration for accurate measurements. The Arduino's 10-bit ADC, with a 0-5V range, provides 1024 steps, translating to approximately 5mV per step or 0.5°C. To enhance resolution, a non-inverting amplifier was employed. The gain of the amplifier, initially set at 11, was recalculated to 4.11 using:

Gain = 1 + (R2/R1)
where R2 = 47kΩ and R1 = 15kΩ

This adjustment ensured the temperature readings were consistent and matched a reference alcohol thermometer. Calibration involved setting two points to determine both offset and slope, aligning the LM35 output with actual temperatures.

Pulse Circuit

Raspberry Pi Integration

Acting as a central broker, the Raspberry Pi facilitates data transmission from the sensor node to the Cloud. This setup supports scalability by enabling multiple sensor nodes to communicate with a single Raspberry Pi, which then uploads the data for remote access and analysis.

Star Network Configuration

Cloud and Web Interface

Data collected by the Raspberry Pi is sent to a cloud server, where it is stored and displayed on a web interface. The front-end, created using HTML and JavaScript, features interactive graphs for real-time data visualisation.

Website Graphs

Experimental Results

Experimental data showed reliable pulse detection with an average rate of 80 BPM, well within normal resting heart rates. Temperature readings, while generally accurate, highlighted areas for improvement in sensor placement and sensitivity.

Pulse Data

Conclusions and Future Directions

UNOsense demonstrates the potential for affordable, DIY healthcare monitoring solutions. Future iterations could enhance accuracy and user-friendliness by integrating more advanced sensors and improving the device form factor.

System in Use

This project underscores the value of open-source, cost-effective technology in addressing global healthcare challenges, paving the way for more accessible and efficient patient monitoring systems.

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