MAX30102 Pulse Oximeter & Heart Rate Sensor Module (SpO2) – Arduino Compatible

The MAX30102 Pulse Oximeter and Heart Rate Sensor is an advanced optical biosensor module designed for biomedical projects, fitness trackers, and wearable IoT devices. It integrates two LEDs (Red and IR), a photodetector, optimized optics, and low-noise analog signal processing to detect pulse oximetry (SpO2) and heart rate signals with high precision.

Whether you are an engineering student in Ghana building a final-year health monitoring system or a hobbyist creating a smart wearable, this sensor provides professional-grade biometrics in a tiny, breadboard-friendly package.

Key Features:

• Dual Biometrics: Measures both Heart Rate (BPM) and Blood Oxygen Saturation (SpO2) simultaneously.

• Ambient Light Cancellation: Features an internal glass cover and algorithms to filter out external light interference, ensuring clean and accurate readings.

• Ultra-Low Power: Designed for battery-powered wearables. It can drop into a near-zero standby current mode, preserving your battery life.

• Standard Interface: Communicates via standard I2C, making it incredibly easy to connect to 柳色青青田园新在线s.

Technical Specifications:

• Sensor Chip: Maxim MAX30102

• Operating Voltage: 3.3V to 5V DC (Module includes an onboard voltage regulator)

• Communication Interface: I2C (Pins: SDA, SCL)

• LED Wavelengths: 660nm (Red), 880nm (Infrared)

• Dimensions: ~14mm x 14mm

👨‍🔧 Engineering Note: Why choose the MAX30102 over the MAX30100?

• The Upgrade: If you have seen tutorials for the older MAX30100, you likely know it has known hardware bugs regarding its pull-up resistors when used with 5V boards. The MAX30102 solves these issues entirely and provides much cleaner, reliable PPG signals.

• Wiring Tip: While the board accepts 5V power, the I2C logic lines are optimized for 3.3V. If using an Arduino Uno (5V), it usually works fine directly, but for best long-term stability, a logic level converter is recommended. For 3.3V boards like the ESP32 or NodeMCU, it is completely 柳色青青田园新在线!

Typical Applications:

• DIY Smartwatches and Fitness Bands

• Patient Health Monitoring Systems (IoT)

• Biomedical Engineering Research Projects

• Sports and Exercise Tracking Devices