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ID: 1193795
zł709.81
Tax included

zł577.08 tax excl.

Kit for measuring muscle activity using electromyography (EMG). Contains everything you need from the MyoWare 2.0 ecosystem to test basic configurations in your applications. SparkFun KIT-25332

4 weeks
On request
Kamami is the official distributor of Sparkfun modules and development kits. All products of this brand in our offer are original and come directly from the manufacturer.

 

Free shipping

free shipping in Poland for all orders over 500 PLN

 

Same day shipping

If your payment will be credited to our account by 11:00

 

14 days for return

Each consumer can return the purchased goods within 14 days

Description

The MyoWare 2.0 kit is an advanced, Arduino-compatible set for measuring muscle activity using electromyography (EMG). It includes everything from the MyoWare 2.0 ecosystem needed to test basic configurations in your applications. The MyoWare 2.0 Wireless Shield is designed to receive data from the MyoWare 2.0 sensor and wirelessly transmit it using the built-in ESP32-WROOM module. The shield also features an integrated LiPo battery that powers both the sensor and the ESP32, enabling remote operation. With snap connectors and low-profile pogo pins, the shield can easily attach to the MyoWare 2.0 sensor. The kit also includes 20 biomedical electrodes for measurements, a mini screwdriver for shield assembly, a USB cable for charging or connecting the microcontroller to a computer, a sensor cable for connecting distant muscle groups, and the MyoWare Cable Shield.

The MyoWare 2.0 Muscle Sensor has been completely redesigned, offering a new compact design and improved circuitry, enhancing the sensor’s performance and reliability. The sensor measures muscle activity via the muscle’s electrical potential, known as surface electromyography (sEMG). During muscle contraction, the sensor processes the filtered and rectified electrical activity of the muscle, generating a signal that indicates the intensity of the contraction. The snap connector system eliminates the need for soldering within the MyoWare 2.0 ecosystem, allowing visualization of muscle activity using the MyoWare 2.0 LED Shield or reading analog results with any Arduino-compatible development board.

The MyoWare 2.0 system enables the creation of devices for medical muscle tension analysis and controllers used in robotics and video games. These modules are prototyping tools and are not intended for diagnosing or treating diseases. Full documentation and numerous examples of use are available on the product page.

Features

MyoWare 2.0 Wireless Shield

  • Compatible with MyoWare 2.0 Muscle Sensors (3 x female connectors - power and EMG Envelope output)
  • Espressif ESP32-WROOM module
  • CH340 USB-to-serial converter
  • 2 x Qwiic connectors
  • ESD protection: protective diodes for USB data lines
  • Protection on VBATT and VUSB lines
  • Resettable PTC fuse (6V, 500mA current)
  • Switches:
    • Power source
    • Power on/off switch
  • Built-in LiPo battery:
    • Nominal capacity: 40mAh
    • Nominal voltage: 3.7V
    • Maximum charging current: 1C (40mA)
  • Charging circuit: MCP73831 for single-cell LiPo, charging current 40mA
  • 3.3V voltage regulator
  • 2.2kΩ pull-up resistors
  • Buttons: reset, general-purpose/bootloader
  • LEDs:
    • PWR - power indicator
    • CHG - charging status
    • 13 - user
    • ENV - Envelope
  • Jumper settings:
    • PWR - power LED
    • SHLD - USB shield
    • REF - reference pin
    • RAW - raw EMG output
    • ENV - Envelope detector output
    • I2C - I2C pull-up resistors
  • Input voltage: 5V via USB Type-C connector
  • Dimensions: 63.5 x 38 mm
  • Weight: 16.7g

MyoWare 2.0 Muscle Sensor

  • Output modes: Raw EMG, Rectified, Envelope
  • Snap connectors:
    • 3 x female (power, EMG Envelope output)
    • 3 x male (electrode input)
  • Adjustable gain
  • Reverse current protection
  • LED indicators: VIN, ENV
  • Power supply: 2.27V to 5.47V
  • Input bias current: 250 pA, max 1 nA
  • Dimensions: 37.57 x 35.9 mm

Kit contains

1193795

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