Related Experiment Video
Updated: May 20, 2025

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision
Published on: March 28, 2025
Design and Testing of a Portable Wireless Multi-Node sEMG System for Synchronous Muscle Signal Acquisition and
Xiaoying Zhu1,2, Chaoxin Li1,2, Xiaoman Liu3
1Division of Life Sciences and Medicine, School of Biomedical Engineering (Suzhou), University of Science and Technology of China, Hefei 230026, China.
Abstract:
Surface electromyography (sEMG) is an important non-invasive method used in muscle function assessment, rehabilitation and human-machine interaction. However, existing commercial devices often lack sufficient channels, making it challenging to simultaneously acquire signals from multiple muscle sites.In this acticle, we design a portable multi-node sEMG acquisition system based on the TCP protocol to overcome the channel limitations of commercial sEMG detection devices. The system employs the STM32L442KCU6 microcontroller as the main control unit, with onboard ADC for analog-to-digital conversion of sEMG signals. Data filtered by analogy filter is transmitted via an ESP8266 WiFi module to the host computer for display and storage. By configuring Bluetooth broadcasting channels, the system can support up to 40 sEMG detection nodes. A gesture recognition algorithm is implemented to identify grasping motions with varying channel configurations. Experimental results demonstrate that with two channels, the Gradient Boosting Decision Tree (GBDT) algorithm achieves a recognition accuracy of 99.4%, effectively detecting grasping motions.
More Related Videos
05:00A Real-Time Wearable Electromyography Measurement System for Small Animals
Published on: November 15, 2024
08:09Multifunctional Setup for Studying Human Motor Control Using Transcranial Magnetic Stimulation, Electromyography, Motion Capture, and Virtual Reality
Published on: September 3, 2015