MyoWare 2.0 Muscle Sensor Development Kit

The MyoWare® 2.0 Muscle Sensor Development Kit is an all-in-one Arduino-compatible electromyography (EMG) sensor kit that provides you with all the boards of the MyoWare 2.0 ecosystem to test different configurations for your application. Depending on your setup, you can visualise the muscles in action with the MyoWare 2.0 LED Shield or read the analogue output using an Arduino-compatible microcontroller. Just snap on a MyoWare 2.0 Shield, add some EMG sensor pads, connect the sensor to a muscle group and flex!

The Sparkfun MyoWare 2.0 muscle sensor included in this kit has been redesigned from the ground up with a new compact and easy-to-use design, and has been updated with the latest and most advanced chipset to improve sensor performance and reliability. The sensor measures muscle activity through the electrical potential of the muscle, commonly known as surface electromyography (EMG or sEMG for short). When the brain commands a muscle to tense, it sends an electrical signal to the muscle to start recruiting motor units (bundles of muscle fibres that generate the muscle's latent force).

The harder you work, the more motor units are recruited to generate more muscle power. The greater the number of motor units, the more the electrical activity of the muscle increases. The MyoWare 2.0 muscle sensor analyses the filtered and rectified electrical activity of the muscle and sends a signal (0-VIN volts, where VIN represents the voltage of the power supply) that represents the intensity with which the muscle is being stretched. An innovative snap-on connector system eliminates the need to solder connections to the MyoWare 2.0 LED Shield. The blue 10-segment bar graph provides a visual representation of the measured signal. The higher the measured muscle activation, the higher the LED on the shield.

Electromyography (EMG) is an old domain that has been used extensively in medicine in the past. It allows to analyse the electrical signals sent by a muscle during activity by placing an electrode and sensory pads on it. Along with the development of microcontrollers and sensors, it has opened up to less specialised and more amateur users, and so here comes the EMG sensor from Advancer Technologies.

Module installation guide

The MyoWare® 2.0 Muscle Sensor Starter Kit is a universal Arduino-compatible electromyography (EMG) sensor kit that provides the bare minimum of the MyoWare 2.0 ecosystem to start measuring and visualising muscle activity. Just plug in the MyoWare 2.0 LED Shield, add some EMG sensor pads, connect the sensor to a muscle group and bend! The kit also includes a mini screwdriver for easy removal of the shields, a USB A to C cable for charging the 40mAh LiPo battery and a MyoWare 2.0 reference cable for connecting large muscle groups.

Features of MyoWare 2.0 Sensor:

• Portable design
• Supply voltage
•     Minimum: +2.27V
•     Typical: +3.3V to +5V
•     Maximum: +5.47V
• Input bias current: 250pA, maximum 1nA
• Reverse polarity protection
• Three output modes
•   Raw EMG
•   Rectified
•   Enclosure
• Expandable via shields
• MyoWare® 2.0 muscle sensor form factor
•    3x female pins (power supply and EMG envelope output)
•    3x male pins (input electrodes)
• LED indicators
•     VIN
•     ENV
• Jumper reference electrode
• Specially designed for microcontrollers
• Adjustable gain
• Board dimensions: 37.57mm x 35.90mm (1.48" x 1.41")

The kit includes:

• 1x MyoWare 2.0 Muscle Sensor (Version 2.0.4)
• 1x MyoWare 2.0 Power Shield
• 1x MyoWare 2.0 LED Shield
• 1x MyoWare 2.0 Link Shield
• 1x TRS 3.5mm Cable
• 1x Reversible USB A to C Cable - 2m
• 1x Disposable Surface EMG/ECG/EKG Electrode - 24mm (10 pack)
• 1x MyoWare 2.0 Cable Shield
• 1x Sensor Cable - Electrode Pads (3 connector)
• 1x MyoWare 2.0 Reference Cable
• 1x MyoWare 2.0 Arduino Shield
• 1x SparkFun RedBoard Plus
• 1x SparkFun Mini Screwdriver

Note: This kit does include a microcontroller - SparkFun RedBoard Plus - compatible with Arduino UNO

The MyoWare 2.0 muscle sensor and LED display are not intended for the diagnosis of disease or other conditions, or the treatment, mitigation or prevention of disease, in humans or other animals.

Links:

• User Manual
• User Manual Advance
• Installation Guide
• Aduino Library
• GitHub - Example code and design files