Quality Controlled EMG Signal Compression using Linear and Non Linear Transforms
Vibha Aggarwal1, Sandeep Gupta2, Manjeet Singh Patterh3, Lakhwinder Kaur4
1Vibha Aggarwal, College of Engineering and Management, Punjabi University Neighborhood Campus, Rampura Phul, Punjab, India.
2Sandeep Gupta*, College of Engineering and Management, Punjabi University Neighborhood Campus, Rampura Phul, Punjab, India.
3Manjeet Singh Patterh, University College of Engineering, Punjabi University, Patiala, Punjab, India.
4Lakhwinder Kaur, University College of Engineering, Punjabi University, Patiala, Punjab, India.
Manuscript received on October 11, 2019. | Revised Manuscript received on 26 October, 2019. | Manuscript published on November 10, 2019. | PP: 5885-5889 | Volume-8 Issue-12, October 2019. | Retrieval Number: L38261081219/2019©BEIESP | DOI: 10.35940/ijitee.L3826.1081219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In today’s era of telemedicine, data and graphical records are required to be transmitted over noisy, power limited and band limited channels. The effective compression is the best alternate to save time and bandwidth. For Electromyogram (EMG) signal, that are huge in data size, must be compressed in such a way so that can be recovered with minimum alterations. This work focused on the tuneable method to compress EMG signals, with linear and non linear transforms. The analysis is based upon compression factor (CF) and percentage root mean square difference (PRD). The results helps to conclude that non linear transform method have precedence over the linear transforms for almost entire range of user defined PRD (UPRD).
Keywords: Compression, EMG signals, Linear transform, Non Linear transform, Quality Control
Scope of the Article: Quality Control