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EMG Muscle Sensor Module

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Out of stock


  • Detects muscle activity (EMG signals) for biomedical and robotics applications.
  • Analog output for real-time signal processing with microcontrollers.
  • Adjustable gain and noise filtering for accurate and stable readings.
  • Compatible with Arduino, Raspberry Pi, and other development boards.
  • Includes electrode pads for easy signal acquisition.
  • Low power consumption, suitable for wearable and experimental projects.
  • Ideal for prosthetics, HCI, gaming, and rehabilitation studies.
  • Note: Images are for illustration purposes only.

 4,800

Out of stock

The EMG Muscle Sensor Module is designed to measure the electrical activity of muscles, allowing users to analyze muscle movement and force in real time. This module is widely used in biomedical engineering, prosthetics, robotics, and human-computer interaction applications. It enables users to interface muscle signals with microcontrollers like Arduino, Raspberry Pi, and other development boards to create interactive projects.

The sensor works by detecting electromyographic (EMG) signals from muscle contractions and converting them into analog output, which can be processed and analyzed. With adjustable gain and signal filtering, it ensures clean and stable readings. The module includes electrode pads that attach to the skin for signal acquisition, making it easy to integrate into various projects.

Key Features:

  • Measures muscle activity (EMG signals) for biomedical and robotic applications.
  • Analog output for real-time signal processing with microcontrollers.
  • Adjustable gain and noise filtering for improved signal accuracy.
  • Compatible with Arduino, Raspberry Pi, and other development boards.
  • Includes electrode pads for easy and comfortable signal acquisition.
  • Low power consumption for battery-operated applications.
  • Compact and easy to integrate into wearable or experimental setups.

Applications:

  • Biomedical research and muscle signal analysis.
  • Robotics and prosthetics for muscle-controlled movements.
  • Human-computer interaction (HCI) and gesture-based interfaces.
  • Gaming and VR projects using muscle-based controls.
  • Athlete performance monitoring and rehabilitation studies.

Note: Images are for illustration purposes only.

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