Pulse Oximeter ESP32 Project

A functional pulse oximeter system built using the ESP32 microcontroller and MAX30102 sensor. This project demonstrates real-time measurement of blood oxygen saturation (SpO₂) and heart rate (BPM), displayed on a 128x64 OLED screen. A second version simulates photoplethysmography (PPG) signals, enabling full signal processing pipeline testing without hardware.

Why This Project Matters

Designed as a showcase of self-taught applied engineering in MedTech, this project reflects my ability to:

• Translate medical sensing theory into working embedded systems
• Apply signal processing techniques to extract physiological metrics
• Work across hardware, firmware, and algorithm development
• Communicate results clearly via UI (OLED) and documentation

As a incoming graduate student in Human Systems Engineering concentraing in Health Sysems with a background in Health Technology, this hands-on build sharpens my technical credibility while reinforcing my user-centric design foundation.

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🛠️ System Overview

Component	Description
Microcontroller	ESP32 DOIT DevKit V1
Sensor	MAX30102 (IR + Red LED, photodetector)
Display	SSD1306 OLED (128x64, I2C)
Output Metrics	SpO₂, BPM
Modes	Hardware mode + Simulated data mode
Communication	I2C for sensor + display
Platform	Arduino IDE

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⚙️ How It Works – Step-by-Step

1. Signal Acquisition

• Hardware Mode: The MAX30102 emits IR and Red light into tissue and captures reflected light to generate raw PPG signals.
• Simulated Mode: Gaussian pulses simulate systolic/diastolic peaks + noise to mimic real PPG waveforms.

2. Filtering

• High-Pass Filter removes baseline wander (DC drift).
• Low-Pass Filter smooths high-frequency noise and stabilizes AC signals.

3. AC/DC Extraction

• AC component = pulsatile flow (from heartbeat)
• DC component = constant light absorption by tissue
• Calculated for both IR and Red signals over a circular buffer.

4. SpO₂ Calculation

Formula used: R = (AC_Red / DC_Red) ÷ (AC_IR / DC_IR) SpO₂ = 110 - 25 × R

This ratio-of-ratios method approximates blood oxygen saturation.

5. Heart Rate Detection

• Peaks in the IR waveform are detected using amplitude thresholds.
• Time between peaks determines BPM:
  BPM = 60 / (time between peaks)

6. Display Output

• Values are shown on the OLED in real-time.
• Simulated mode outputs signals to Serial Plotter.

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Modes

Hardware Version

• Uses real data from MAX30102
• Outputs live BPM/SpO₂ to OLED

Simulated Version

• No sensor required
• Generates synthetic Red/IR PPG signals
• Follows same filtering and calculation logic
• Outputs to Serial Plotter for visualization

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📁 Files Included

• hardware_version.ino
  Final implementation for real-time BPM + SpO₂ output using actual hardware.

• simulated_version.ino
  Simulated PPG generator + full signal processing pipeline, with detailed inline comments.

• README.md
  Full documentation and system architecture.

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Setup Instructions

Requirements

• Libraries:
  • SparkFun MAX3010x
  • Adafruit GFX
  • Adafruit SSD1306

Hardware Wiring (I2C):

ESP32 Pin	MAX30102	OLED Display
GPIO 21	SDA	SDA
GPIO 22	SCL	SCL
3.3V	VIN	VCC
GND	GND	GND

Uploading

1. Open Arduino IDE
2. Select board: ESP32 Dev Module
3. Install required libraries via Library Manager
4. Upload hardware_version.ino or simulated_version.ino
5. Use OLED or Serial Monitor/Plotter for output

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Skills Demonstrated

• Embedded firmware design: Programming microcontrollers to run device functions.
• Digital signal processing: Interpreting sensor data to produce meaningful measurements.
• Biomedical sensing fundamentals: Understanding how physiological signals like heart rate and oxygen saturation are measured.
• Sensor interfacing (I2C): Connecting and communicating with sensors.
• Real-time system debugging: Troubleshooting the device to ensure reliable performance.
• Simulation-driven development: Using software simulations to test and refine the system before building hardware.

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📌 License

This project is open-source under the MIT License.