Wavelet thresholding technique for sEMG denoising by baseline estimation
journal contributionposted on 21.05.2015, 09:06 by Luca Bartolomeo, Massimiliano ZeccaMassimiliano Zecca, Salvatore Sessa, Atsuo Takanishi
The surface electromyography (sEMG) signal is affected by different sources of noises: current technology is considerably robust to the interferences of the power line or cable motion artefacts, but still there are many limitations in denoising the baseline. In this paper, we introduce a new technique, named baseline adaptive denoising algorithm (BADA), for denoising the sEMG signal by wavelet thresholding procedure. In particular, the thresholds are estimated using the same baseline signal with fixed and adaptive techniques. Eventually, we verify that the proposed adaptive method performs better than the standard Donoho technique and different variations, in term of noise cancellation and distortion of the signal, quantified by a new suggested indicator of the denoising quality. Copyright © 2012 Inderscience Enterprises Ltd.
This research has been supported by the G-COE Global Robot Academia Program in Waseda University, Japan and partially by a Grant by STMicroelectronics. This research has been conducted at Humanoid Robotics Institute, in collaboration with the G-COE Global Robot Academia. The authors would like to express their gratitude to Okino Industries LTD, Japan ROBOTECH LTD, SolidWorks Corp, Dyden, for their support to the research.
- Mechanical, Electrical and Manufacturing Engineering