期刊文献+

基于ADS1294的表面肌电信号采集系统的设计 被引量:3

Design of ADS1294 SEMG acquisition system
下载PDF
导出
摘要 目的:设计并实现一种表面肌电信号采集系统。方法:由基于ADS1294数模转换芯片的前端信号采集模块、基于LPC2368的微处理器模块以及运行在Windows环境下的上位机控制程序构成整套系统。由上位机程序发出控制命令,经串口传输到微处理器,从而实现对前端采集模块的控制,将采集到的信号经过微处理器模块最终传输到个人计算机上进行显示与保存。结果:系统能够实时从人体采集多路表面肌电信号,在上位机程序中动态显示,并将信号转换成24位μV级数据存储在个人计算机上。结论:经过大量临床试验表明,系统具有体积小、功耗低、精度高以及操作直观等优点,可以获得多路清晰的表面肌电信号,可以应用于肌肉临床诊断、康复医学及运动医学等领域。 Objective To design and implement one kind of SEMG signal acquisition system. Methods The system consisted of three parts, namely, signal acquisition module based on digital-analog conversion chip ADS1294, LPC2368 microprocessor module and PC application program under Windows. The control commands were sent from PC application program first, and transmitted to the microprocessor to control the signal acquisition module, and then the acquired signals were displayed and stored on PC. Results The system could acquire multiplex real-time SEMGs, display in the PC program dynamically, and convert signals into 24 μV level data and store them on PC. Conclusion The system is proved to have low volume, low power to consumption, high precision and easy operation, which can obtain multiplex SEMGs and thus can be used for diagnosis of muscle disease, rehabilitation medicine and sport medicine.
出处 《医疗卫生装备》 CAS 2015年第1期5-7,28,共4页 Chinese Medical Equipment Journal
基金 国家自然科学基金资助项目(61203117)
关键词 表面肌电图 ADS1294 LPC2368 SEMG ADS1294 LPC2368
  • 相关文献

参考文献11

二级参考文献58

共引文献102

同被引文献30

  • 1陈思佳,罗志增.基于长短时记忆和卷积神经网络的手势肌电识别研究[J].仪器仪表学报,2021,42(2):162-170. 被引量:25
  • 2石欣,范智瑞,张杰毅,徐淑源,蔡建宁.基于LMS-随机森林的肌电信号下肢动作快速分类[J].仪器仪表学报,2020,41(6):218-224. 被引量:18
  • 3卢海峰,江朝元,阳小光.基于串口通信的在线监测系统关键技术研究[J].仪器仪表学报,2006,27(z3):2043-2044. 被引量:20
  • 4谈华暠,刘海林.盲稀疏源信号分离算法的恢复性研究[J].广东工业大学学报,2007,24(3):28-31. 被引量:3
  • 5Turan S, Turan O M, Berg C, et al. Computerized fetal heart rate analysis, Doppler ultrasound and biophysical pro- file score in the prediction of acid-base status of growth - restricted fetuses [ J ]. Ultrasound in Obstetrics & Gynecolo- gy, 2007, 30 (5) : 750-756.
  • 6Graatsma E M, Jacod B C, Van Egmond L A J, et ah Fe- tal electrocardiography: feasibility of long term fetal heart rate recordings [ J ]. B JOG : An International Journal of Ob- stetrics & Gynaecology, 2009, 116(2): 334-338.
  • 7Abdulhay E W, Oweis R J, Alhaddad A M, et al. Review article:non-Invasive fetal heart rate monitoring techniques [ J ]. Biomedical Science and Engineering,2014,2 ( 3 ) : 53-67.
  • 8Gruber P, Meyer-Base A, Foo S, et al. ICA, kernel meth- ods and nonnegativity: New paradegms for dynamical com- ponent analysis of fMRI data[ J]. Engineering Applications of Artificial Intelligence, 2009, 22 (4) : 497-504.
  • 9Wenting S, Bin F, Pu W, et al. FECG extraction based on BSS of sparse signal [ C ] //Bioinformatics and Biomedical Engineering, ICBBE 2008. The 2nd International Confer- ence on. Shanghai:IEEE, 2008 : 1457-1460.
  • 10Lee T W, Lewicki M S, Girolami M, et al. Blind source separation of more sources than mixtures using overeomplete representations [ J ]. Signal Processing Letters, IEEE, 1999, 6(4): 87-90.

引证文献3

二级引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部