Multi-Channel EMG Sensor Kit – Biomedical Signal Acquisition System for Robotics & Research

Our professional-grade EMG (Electromyography) sensor kit captures and processes muscle electrical signals for research, robotics control, and biomedical applications. This versatile system enables real-time monitoring of muscle activity and translates biological signals into control commands for various external devices.

Technical Specifications

• Processor Options: STM32F1 series or Arduino UNO R3

• Signal Type: Analog sensor output

• Sampling Rate: 600-10,000 Hz (adjustable)

• Material Composition: Mixed materials

• Origin: Mainland China

• Operating Principle: Biological signal sensing

Available Configurations

Six-Channel Systems

• Arduino Wireless Transmission Kit
  Wireless data transmission compatible with Arduino IDE

• Arduino Serial Transmission Kit
  Wired serial communication for stable data transfer

• STM32 Wireless Transmission Kit
  High-performance STM32 processor with wireless capability

• STM32 Robotic Hand Control Kit
  Complete setup for muscle-controlled robotic manipulation

• STM32 Stepper Motor Control Kit
  Precision motor control through muscle signals

Advanced Multi-Channel Systems

• Twelve-Channel STM32 Acquisition Kit
  Expanded capability for complex muscle group monitoring

• Eighteen-Channel STM32 Acquisition Kit
  Professional-grade system for research applications

• Twenty-Four-Channel STM32 Acquisition Kit
  Comprehensive solution for advanced biomechanical studies

Key Features & Capabilities

Real-Time Data Visualization

• Simultaneous multi-channel display

• Individual channel monitoring

• Histogram representation for comparative analysis

• Real-time signal strength indicators

Advanced Data Management

• Snapshot functionality with automatic data recording

• Configurable data point storage (1000+ points)

• Data export for secondary analysis and replay

• Compatible with MATLAB for advanced processing

Hardware Specifications

• Raw EMG signal output

• LED indicators for signal strength

• Programmable control buttons

• Adjustable sensitivity and gain

• Expandable electrode connections

Application Examples

Robotic Hand Control
Convert muscle signals into precise robotic movements using PWM output for proportional control.

Stepper Motor Operation
Translate muscle activity into rotational movement with adjustable threshold sensitivity.

Musical Interface Creation
Develop bio-signal controlled instruments where muscle intensity determines note duration and character.

Research & Development

• Pattern recognition for fine motor control

• Signal processing applications (Kalman filtering, PCA, ICA)

• Biomechanical movement analysis

• Rehabilitation engineering research

Development Environment

• Arduino Version: Arduino IDE compatible

• STM32 Version: KEIL5 compilation environment

• Programming Support: Complete source code and tutorials included

• Customization: Available upon request

Software Features

• Multi-format data display (graphical, numerical)

• Configurable recording parameters

• Text and log file output

• Real-time plot commands

• Channel synchronization

Important Notes

• Designed for research and development purposes only

• Not intended for medical diagnosis or clinical applications

• Comprehensive technical support included

• Custom configurations available

• Suitable for educational and research institutions

Ideal For

• Biomedical engineering projects

• Robotics and prosthetics development

• Sports science research

• Human-computer interaction studies

• Academic research and teaching laboratories

• Maker projects and prototyping

This EMG sensor system provides researchers, engineers, and developers with a robust platform for capturing and utilizing biological signals, offering exceptional flexibility across various applications from basic educational demonstrations to advanced research projects.