News Updates Sunday 23rd Oct 2016 :
  • Welcome to International Press Corporation, world's leading publishers, We have served more than 10000+ authors
  • Articles are invited in engineering, science, technology, management, industrial engg, biotechnology etc.
  • Paper submission last date of Sept/Oct 2016 issue is 25 Oct 2016, Submit online or at
  • Our journals are indexed in University of Regensburg Germany, Google Scholar, Cross Reference data bases
  • Applications for reviewers are invited and can be sent directly to concerned editor's mail

Acquisition of EMG signals to recognize multiple Hand Gestures for Prosthesis Robotic Hand-A Review

Author : Sumit A. Raurale

Pages : 65-70
Download PDF

Robotic prosthesis hand amputees are highly benefited, which would allow the various hand gestures based on wrist and fingers movements. In the field of Biomedical signal processing, development of an advanced human–machine interface has been an interesting research topic in the field of rehabilitation, in which electromyography (EMG) signals, have a vital role to play. EMG signal is an electrical activity of Muscles and usually represented as a function of time, defined in terms of amplitude, frequency and phase. EMG signal based reliable and efficient hand gesture recognition can help to develop good human computer interface which in turn will increase the quality of life of the disabled or aged people. Acquisition and analysis of EMG signals concerns with the detection, processing, feature extraction, classification and application for control human-assisting Robots or prosthetic applications. This paper reviews recent research and development of hand prosthetic for multiple hand gestures based on wrist-hand mobility subsequent from the EMG signals. To identify the effectiveness of hand prosthesis, forearm muscles are being considered for better exploitation of EMG signals and classification of movements is done by Wavelet transform followed by efficient time-frequency featuring in Artificial Neural Networks (ANN).

Keywords: Artificial Neural Networks, Classification, EMG signal, Feature extraction, Wavelet transform.

Article published in International Journal of Current  Engineering  and Technology, Vol.4,No.1 (Feb- 2014)





Call for Papers
  1. IJCET- Sept/Oct-2016 Issue

    Submission Last Date
    25 Oct 2016
  2. IJTT-Sept-2016
  3. IJAIE-Sept-2016
  4. IJCSB-Sept-2016
  • Inpressco Google Scholar
  • Inpressco Science Central
  • Inpressco Global impact factor
  • Inpressco aap

International Press corporation is licensed under a Creative Commons Attribution-Non Commercial NoDerivs 3.0 Unported License
©2010-2016 INPRESSCO® All Rights Reserved