Design and Testing of a Portable Wireless Multi-Node sEMG System for Synchronous Muscle Signal Acquisition and Gesture Recognition.

IF 3 3区 工程技术 Q2 CHEMISTRY, ANALYTICAL
Micromachines Pub Date : 2025-02-27 DOI:10.3390/mi16030279
Xiaoying Zhu, Chaoxin Li, Xiaoman Liu, Yao Tong, Chang Liu, Kai Guo
{"title":"Design and Testing of a Portable Wireless Multi-Node sEMG System for Synchronous Muscle Signal Acquisition and Gesture Recognition.","authors":"Xiaoying Zhu, Chaoxin Li, Xiaoman Liu, Yao Tong, Chang Liu, Kai Guo","doi":"10.3390/mi16030279","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":18508,"journal":{"name":"Micromachines","volume":"16 3","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11944688/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Micromachines","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.3390/mi16030279","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
引用次数: 0

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.

用于同步肌肉信号采集和手势识别的便携式无线多节点表面肌电信号系统的设计与测试。
表面肌电图(sEMG)是一种重要的无创方法,用于肌肉功能评估、康复和人机交互。然而,现有的商用设备往往缺乏足够的通道,这使得同时从多个肌肉部位获取信号具有挑战性。在本文中,我们设计了一个基于TCP协议的便携式多节点表面肌电信号采集系统,以克服商用表面肌电信号检测设备的信道限制。该系统采用STM32L442KCU6微控制器作为主控单元,板载ADC对表面肌电信号进行模数转换。通过类比滤波器滤波后的数据通过ESP8266 WiFi模块传输到上位机显示和存储。通过配置蓝牙广播通道,系统可以支持多达40个表面肌电信号检测节点。实现了一种用于识别具有不同通道配置的抓取动作的手势识别算法。实验结果表明,在两个通道下,梯度增强决策树(GBDT)算法的识别准确率达到99.4%,能够有效地检测抓取动作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Micromachines
Micromachines NANOSCIENCE & NANOTECHNOLOGY-INSTRUMENTS & INSTRUMENTATION
CiteScore
5.20
自引率
14.70%
发文量
1862
审稿时长
16.31 days
期刊介绍: Micromachines (ISSN 2072-666X) is an international, peer-reviewed open access journal which provides an advanced forum for studies related to micro-scaled machines and micromachinery. It publishes reviews, regular research papers and short communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信