88
Views
7
CrossRef citations to date
0
Altmetric
Innovation

Comparative study of wavelet denoising in myoelectric control applications

&
Pages 80-86 | Received 23 May 2015, Accepted 03 Jan 2016, Published online: 18 Feb 2016

References

  • Veer K. A technique for classification and decomposition of muscle signal for control of myoelectric prostheses based on wavelet statistical classifier. Measurement. 2015;60:283–291.
  • Phinyomark A, Phukpattaranont P, Limsakul C. Computational intelligence in electromyography analysis – a perspective on current applications and future challenges. Croatia: InTech; 2012. Chapter 8, The usefulness of mean and median frequencies in electromyography analysis; p. 195–220.
  • Veer K. Experimental study and characterization of SEMG signals for upper limbs. Fluct Noise Lett. 2015;14:1–18.
  • Ryait HS, Arora AS, Agarwal R. Interpretations of wrist operations from surface-EMG signals at different locations on arm along with acupressure points. IEEE Trans Biomed Circ Syst. 2010;4:101–111.
  • Phinyomark A, Phukpattaranont P, Limsakul C. Feature extraction and reduction of wavelet transform coefficients for EMG pattern classification. Electron Electr Engineer Signal Technol. 2012;6:27–32.
  • Veer K, Agarwal R. Wavelet and short-time fourier transform comparison-based analysis of myoelectric signals. J Appl Stat. 2015;42:1591–1601.
  • Phinyomark A, Llimsakul C, Phukpattaranont P. Optimal wavelet functions in wavelet denoising for multifunction myoelectric control. ECTI Trans Electr Eng Electron Commun. 2010;8:43–52.
  • Veer K. Wavelet transform-based classification of electromyogram signals using an ANOVA technique. Neurophysiology. 2015;47:302–309.
  • Englehart K, Hudgins B, Parker PA. A Wavelet-based continuous classification scheme for multifunction myoelectric control. IEEE Trans BME. 2001;48:302–311.
  • Lascu M, Lascu D. Graphical programming based biomedical signal acquisition and processing. Int J Circ Syst Sign Proc. 2007;1:317–326.
  • Sharma T, Veer K. Wavelet based feature extraction of electromyogram signal for denoising. Int J Adv Res Comp Engineer Technol. 2014;3:2623–2627.
  • Jiang C-F, Kuo S-L. A comparative study of wavelet denoising of surface electromyographic signals. Proceedings of the 29th Annual International Conference of the IEEE EMBS; 2007 Aug 23–26; Lyon, France; 2007.
  • Zhang X, Wang Y, Han PSR. Wavelet transform theory and its application in EMG signal processing. Seventh International Conference on Fuzzy Systems and Knowledge Discovery. 2010 Aug 10–12; Yantai, China; 2010.
  • Veer K, Agarwal R. Wavelet denoising and evaluation of electromyogram signal using statistical algorithm. Int J Biomed Engineer Technol. 2014;16:293–305.
  • Englehart K, Hudgins B, Parker PA, et al. Classification of the myoelectric signal using time-frequency based representations. Med Engineer Phys. 1999;21:431–438.
  • De luca SA. Mohamed RH. Serge. Median frequency of the myoelectric signal: Effect of hand dominance. Eur J Appl Physiol. 1986;55:457–464.
  • Lawrence JH, De Luca CJ. Myoelectric signal versus force relationship in different human muscles. J Appl Physiol. 1983;54:1653–1659.
  • Navarro CJ, Leon-Vargas F, Perez BJ. EMG-based system for basic hand movement recognition. DYNA. 2012;79:41–49.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.