期刊文献+

The SVD of the EMG basis on the FFT of the Kaiser window 被引量:3

The SVD of the EMG basis on the FFT of the Kaiser window
下载PDF
导出
摘要 The EMG signal is a present field of research which is a driving force in sources of rehabilitating robots. The FFT with Kaiser Window was used in this paper to analyze the spectral characteristics of the EMG signal according to the characteristic of time changing and nonlinearity for the EMG signal and good results have been obtained. The singular value expressing the property of every EMG signal at each channel was taken out. It offered important data for the actual control of rehabilitating robots. The EMG signal is a present field of research which is a driving force in sources of rehabilitating robots. The FFT with Kaiser Window was used in this paper to analyze the spectral characteristics of the EMG signal according to the characteristic of time changing and nonlinearity for the EMG signal and good results have been obtained. The singular value expressing the property of every EMG signal at each channel was taken out. It offered important data for the actual control of rehabilitating robots.
出处 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2005年第3期275-277,共3页 哈尔滨工业大学学报(英文版)
关键词 EMG信号 光谱分析 FFT 快速傅氏变换算法 SVD 机器人技术 EMG signal spectrum analysis FFT with Kaiser SVD
  • 相关文献

参考文献2

二级参考文献23

  • 1[1]DARIO P, GUGLIELMELLI E, LASCHI C. Humanoids and personal robots: Design and experiments [ J ] . Journal of Robotic Systems, 2001,18 (12): 673 - 690.
  • 2[4]TSUJI L T. Pattern classification of time-series EMG signals using neural networks [ J ]. International Journal of Adaptive Control and Signal Processing, 2000, 14:829 -848.
  • 3[5]LATERZ F. Analysis of EMG signals by means of the matched wavelet transform [ J ]. Electronics Letters,1997,5:357 - 359.
  • 4[7]MORIN E L. Identifying the EMG- force relationship [ J]. IEEE EMBC and CMBEC, 1995,2:1397 - 1398.
  • 5[8]CLANCY E A. Relating agonist - antagonist electromyograms to joint torque during isometric, quasi-isotonic,nonfatiguing contractions [ J ]. IEEE-Trans Bioned Eng,1997,44(10): 1024 - 1028.
  • 6[9]MATHIEU P A. EMG and Kinematics of normal subjets performing trunk flexion/extensions freely in space [ J ].Journal of Electromyography and Kinesiology, 2000, 10(3): 197 -209.
  • 7[10]LUH J J. Using time-varying autogressive filter to improve EMG amplitude estimator[J]. IEEE- EMBC and CMBEC, 1995, 2:1343 - 1344.
  • 8[11]KERMANI M Z. EMG featureselection for movement control of a cybenetic arm. Cybernetics and Systems [ J ]. An International Journal, 1995,26:189 - 210.
  • 9[12]YANAETAL K. Surface electromyogram recruitment analysis using higher order spectrum[J]. IEEE -EMBC and CMBEC, 1995,2:1345 - 1346.
  • 10[13]ZAHEDI E. Graphical simulation of artificial hand motion with fuzzy EMG pattern recognition [ A ]. Proceedings RC IEEE- EMBC&14THBMESI[C]. [s.l.]: [ s.n.], 1995.

共引文献52

同被引文献15

  • 1吕广明,孙立宁,彭龙刚.康复机器人技术发展现状及关键技术分析[J].哈尔滨工业大学学报,2004,36(9):1224-1227. 被引量:45
  • 2PAOLO Dario, GUGLIELMELLI Eugenio, CECILIA Laschi. Humanoids and personal robots: design and experiments[J]. Journal of Robotic Systems,2001,18(12):673-690.
  • 3LEE Seung-Hi, KIM Young-Hoon, CHUNG Chung-choo. Multirate digital control system design[A]. Proceedings of the 2002 Anchorage[C]. AK, U.S, 2002,3:1 861-1 866.
  • 4GHORBANI A A, OWRANGH K. Stacked generalization in neural networks: generalization on statistically neutral problems[A]. Proceedings of IJCNN '01[C]. Washington, DC, 2001,3:1 715-1 720.
  • 5DEL VECCHIO D,MARINO R,TOMEI P.Adaptive state feedback control by orthogonal approximation functions[J].International Journal of Adaptive Control and Signal Processing,2002,16 (9):635-652.
  • 6YOUNG H K,FRANK L L.Neural network output feedback control of robot manipulators[J].IEEE Transactions on Robotics and Automation,1999,15(2):301 -309.
  • 7吕广明,孙立宁,陆念力.五自由度康复机器人的BP网络控制模型研究[C]//中国控制与决策学术年会.哈尔滨:[s.n.],2005:2024-2026.
  • 8KUC Tae-yong,BAEK Seung-min,SOHN Kyung-oh,et al.Intelligent control of DC motor driven mechanicalsystems:a robust learning control approach[J].International Journal of Robust and Nonlinear Control,2002,13(1),71-90.
  • 9郑亚虹.人机工程学理论在机械设计中的应用[J].江苏广播电视大学学报,1999,0(4):102-104. 被引量:2
  • 10蔡立羽,王志中,张海虹.基于短时傅里叶变换的肌电信号识别方法[J].中国医疗器械杂志,2000,24(3):133-136. 被引量:12

引证文献3

二级引证文献9

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