EMG Muscle Signal Starter Kit Kit with Arduino Uno + LED
Build a Real-Time Forearm EMG Visualizer with Arduino Uno & OLED
Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.
Biofeedback systems start with a single muscle. This kit puts a working EMG capture and classification pipeline on your desk — one that reads your forearm signals, draws the envelope in real time on a crisp OLED, and lights up an LED the moment you flex. It’s the same signal chain used in prosthetics research and human-computer interaction, stripped down to its essentials so you can understand every component.
What You'll Build
By the end of the four-hour build, you’ll have a compact device that reads surface EMG through electrode patches, amplifies and filters the faint muscle impulses with the BioAmp Candy, then feeds an Arduino Uno running envelope detection. The OLED displays the live envelope trace and simultaneously classifies your forearm state — flex or rest — triggering an on‑board LED. It’s a complete, stand‑alone bio‑monitor you can wear or embed in a larger project.
What You'll Learn
- Capture surface electromyography (EMG) using medical‑grade dry electrode patches
- Amplify and band‑pass filter biological signals with the Muscle BioAmp Candy
- Program envelope detection and real‑time waveform display on a 0.96‑inch OLED
- Implement threshold‑based classification to reliably distinguish muscle flexion from rest
Kit Contents
| Component | Quantity |
|---|---|
| Arduino Uno R3 | 1 |
| Muscle BioAmp Candy | 1 |
| Electrode Patch | 6 |
| 0.96in OLED | 1 |
| 10kΩ Resistors | 5 |
| 100nF Caps | 5 |
| 400-pt Breadboard | 1 |
| M-M Wires | 20 |
| 9V Battery Snap | 1 |
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 intermediate makers who want to move beyond blinking LEDs. Ideal for CBSE Class 11–12 students exploring biomedical instrumentation, B.Tech ECE/EEE undergraduates building mini projects, and Smart India Hackathon teams prototyping human‑machine interfaces. ATL Tinkering Lab mentors and hobbyists at VIT, BITS, NIT or IIT campuses will find the classification logic especially useful as a foundation for gesture‑controlled wearables or assistive devices.
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 box to open your AI build companion — it walks you through every wiring step and code block. If you still need human help, WhatsApp us and a real Indian maker will reply within an hour.
Can I use this kit to control a prosthetic hand?
This kit focuses on signal acquisition and classification; the built-in LED demonstrates the flex/rest output. You can extend it to drive a servo motor or prosthetic hand with an additional motor driver — the core EMG processing remains identical.
Do I need prior electronics knowledge?
Basic familiarity with Arduino and a breadboard is recommended. The AI companion explains each circuit block from scratch, so even if you’ve only completed a few beginner projects you can follow along and learn.
How accurate is the flex/rest classification?
The threshold-based classifier reliably detects deliberate forearm contractions. It’s intended for binary states; more nuanced gesture recognition can be achieved by logging serial data and training a simple model later — the hardware is fully capable.
Muscle BioAmp Candy captures forearm EMG. OLED shows envelope signal and classifies flex vs rest state.
What's in this kit
- Arduino Uno R3
- Muscle BioAmp Candy
- Electrode Patch x6
- 0.96in OLED
- 10kΩ Resistors x5
- 100nF Caps x5
- 400-pt Breadboard
- M-M Wires x20
- 9V Battery Snap
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