ESP32 Athlete Tracker Kit - Build a PPG Glucose Trend Monitor
ESP32 Athlete Performance Tracker Kit - Build a Wearable PPG Glucose Trend Monitor
Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.
For an athlete pushing endurance limits, subtle shifts in blood glucose can make or break a performance. This advanced ESP32 kit lets you build a custom wearable that uses dual near-infrared LEDs and photodiodes to extract photoplethysmography (PPG) waveform features those shifts leave behind-without a traditional continuous glucose monitor. You'll design a multi-wavelength optical front-end, sample weak biosignals, and train your own algorithms to correlate PPG dynamics with metabolic trends seen during training, recovery, and competition.
What You'll Build
A fully functional finger-worn optical sensor module streaming raw PPG data to the ESP32. Waveforms are timestamped via the DS3231 real-time clock, logged to a MicroSD card, and summarised on a 0.96-inch OLED display showing real-time trend indicators. The prototype becomes your personal biosignal capture rig, ready to feed long-term glucose-correlation analysis or later be packaged in the included enclosure as a field-ready wearable.
What You'll Learn
- Designing dual-wavelength PPG front-ends with transimpedance amplification using the LM358 op-amp to extract minute light-induced currents from the BPW34 photodiodes.
- Sampling and digital filtering of physiological signals on the ESP32, rejecting motion artefacts and ambient light interference to isolate clean waveform morphology.
- Extracting waveform features such as AC/DC ratio, rise time, and dicrotic notch characteristics that research has linked to glucose-related metabolic changes.
- Logging time-stamped sensor data to a MicroSD module for offline analysis, allowing you to build statistical models or train machine learning pipelines for trend prediction.
Kit Contents
| Component | Quantity |
|---|---|
| ESP32 Dev Board | x1 |
| MAX30102 | x1 |
| 850nm LED | x2 |
| BPW34 Photodiode | x2 |
| LM358 Op-Amp | x2 |
| DS3231 RTC | x1 |
| MicroSD Module | x1 |
| 0.96in OLED | x1 |
| 10k? Resistors | x10 |
| 100nF Caps | x10 |
| 3.7V LiPo 1000mAh | x1 |
| TP4056 Module | x1 |
| PCB Prototype Board | x3 |
| Enclosure Box | x1 |
| Soldering Iron | x1 |
| Solder Wire | x1 |
Why Buy This Kit Instead of Sourcing Parts Separately
| Factor | Sourcing Separately | Compoden Kit |
|---|---|---|
| Compatibility checks | You verify every part | Pre-tested as a system |
| Build support | Forums and scattered tutorials | AI companion trained on this exact project |
| Time to first working build | Days of debugging | Hours, with step-by-step guidance |
| Shipping coordination | Multiple sellers, multiple delays | One shipment from Bengaluru in 3-5 days |
Who This Kit Is For
Designed for B.Tech and M.Tech students in ECE and EEE final-year projects, researchers at IITs and NITs exploring non-invasive biosensing, and Smart India Hackathon teams building athlete performance monitors. It also suits sports scientists and hardware engineers who want a reproducible platform for capturing PPG-glucose correlation data before moving to clinical validation.
Built and Backed by Compoden
Every Compoden kit ships with an AI build companion trained on this exact project - accessible via a QR code on the box, with WhatsApp and email backup. We've spent 10 years building projects for makers, schools, and institutions across India. If a part fails because of a manufacturing defect, replace it free within 7 days.
What if I get stuck during the build?
Scan the QR code on the enclosure to launch the AI companion, which holds step-by-step diagnostics for this exact circuit. If you still need a human, message us on WhatsApp; we answer within hours.
Does this kit measure blood glucose levels directly?
No, it extracts PPG waveform features that research correlates with glucose trends. The output is not a medical-grade reading and should not be used for clinical decisions-it's a development platform for sports performance research.
What software skills are required?
You'll program the ESP32 in Arduino IDE (C++) for data acquisition and real-time display. For offline feature extraction and trend modelling, you can use Python with libraries like NumPy and scikit-learn-the companion AI includes starter code.
Can I train a machine learning model with the logged data?
Absolutely. The timestamped CSV files on the MicroSD card are ready for feature extraction. With enough controlled trials, you can build a custom predictor, though clinical-grade accuracy requires rigorous calibration and validation beyond the kit's scope.
Sports Performance - Near-IR LED + photodiode on finger measures photoplethysmography waveform features correlated with glucose trends.
What's in this kit
- ESP32 Dev Board
- MAX30102
- 850nm LED x2
- BPW34 Photodiode x2
- LM358 Op-Amp x2
- DS3231 RTC
- MicroSD Module
- 0.96in OLED
- 10k? Resistors x10
- 100nF Caps x10
- 3.7V LiPo 1000mAh
- TP4056 Module
- PCB Prototype Board x3
- Enclosure Box
- Soldering Iron
- Solder Wire
Choose your assembly option:
- Soldering Kit - 25W soldering iron, 60/40 solder wire, flux, and small perfboard for permanent assembly.
- Breadboard Combo - 800-point full-size breadboard with 65-piece jumper wire pack for solderless prototyping.
Other projects you can build
Shipping Information
- Prepaid Orders: ₹75 for orders up to ₹999, FREE shipping above ₹999
- COD Orders: ₹125 shipping + ₹50 COD fee = ₹175 total
- Delivery Timeline: Dispatch in 1-2 days, delivery in 2-7 days depending on location
Returns & Warranty
- 7-Day Return: Manufacturing defects only (approval required)
- Warranty: 7 days from delivery
- Non-Returnable: Batteries, consumables, cut wires, clearance items