AI Gait Disorder Classifier Kit with ESP32 + MPU6050
AI Gait Disorder Classifier Kit with ESP32 + MPU6050 — Build a Wearable Gait Analysis System
Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.
Transform three MPU6050 inertial measurement units into a wearable array that captures full 6DOF motion data from the hip, knee, and ankle simultaneously. Using TensorFlow Lite, the ESP32 classifies your walking pattern in real time—ideal for prototyping assistive health devices, biomedical research, or Smart India Hackathon projects that demand portable, on-device AI.
What You'll Build
You’ll assemble three sensor nodes strapped to the lower body, synchronise them through an I2C multiplexer, and stream fused orientation and acceleration data to the ESP32. The device logs timestamped gait cycles to a microSD card, displays classification results on the OLED, and runs a trained TensorFlow Lite model to distinguish normal from abnormal gait without a cloud connection.
What You'll Learn
- Synchronise multiple MPU6050 sensors via the TCA9548A I2C multiplexer on a shared bus
- Extract time-domain and frequency-domain features from 6DOF gait signals for machine learning
- Train a TensorFlow Lite model for time-series classification and deploy on ESP32
- Build a battery-powered wearable with real-time OLED feedback and microSD data logging
Kit Contents
| Component | Quantity |
|---|---|
| ESP32 Dev Board | x1 |
| MPU6050 | x3 |
| TCA9548A I2C Mux | x1 |
| DS3231 RTC | x1 |
| MicroSD Module | x1 |
| 0.96in OLED | x1 |
| TP4056 Module | x1 |
| 3.7V LiPo 1000mAh | x1 |
| 4.7kΩ Resistors | x10 |
| 100nF Caps | x15 |
| PCB Prototype Board | x3 |
| Velcro Straps | x3 |
| 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 biomedical engineering and ECE students tackling final-year capstone projects on motion analysis, researchers prototyping wearable diagnostic tools, and healthcare IoT teams competing in Smart India Hackathon. If you're at IIT, NIT, VIT, BITS, or a medical-device startup and need a ready-to-assemble IMU array that runs edge AI, this kit removes the sourcing and integration guesswork.
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?
Our AI builder is trained on this exact gait classifier circuit, and our WhatsApp support line connects you with engineers who have assembled and debugged the same project. You’ll typically get a reply within a few hours.
Do I need prior experience with TensorFlow Lite?
This kit assumes you have intermediate-to-advanced experience with ESP32/Arduino and basic machine learning concepts. The AI companion will guide you through model training in a Jupyter notebook and conversion to TensorFlow Lite, but familiarity with Python is recommended.
Can I use this kit for clinical diagnosis?
No, this kit is for educational and research purposes only. It demonstrates the principle of wearable gait classification but is not a certified medical device. Do not rely on its output for patient care or diagnosis.
Will the Velcro straps fit all leg sizes?
The included straps adjust up to a 55 cm circumference, fitting most adult legs securely. For larger limbs, you can easily substitute longer straps from local haberdasheries; the sensor casing design remains unchanged.
IMU array at hip, knee and ankle captures 6DOF gait data. TensorFlow Lite classifies normal vs. abnormal gait.
What's in this kit
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