TY - JOUR

T1 - Linux-based Embedded System for Wavelet Denoising and Monitoring of sEMG Signals using an Axiomatic Seminorm

AU - Schimmack, Manuel

AU - Mercorelli, Paolo

N1 - Conference code: 13

PY - 2015/6/1

Y1 - 2015/6/1

N2 - This paper deals with the noise detection of discrete sEMG signals using wavelets. More specifically, it compares the usefullness of the Haars and Daubechies wavelets for the denoising and compression of the digitalized biosignal. The work is based upon the Discrete Wavelet Transform (DWT) version of Wavelet Package Transform (WPT). A denoising algorithm is proposed to detect unavoidable measured noise in the acquired data. With the help of a seminorm the noise of a sequence is defined. Using this norm it is possible to rearrange the wavelet basis, which can illuminate the differences between the coherent and incoherent parts of the sequence, where incoherent refers to the part of the signal that has either no information or contradictory information. In effect, the procedure looks for the subspace characterised either by small components or by opposing components in the wavelet domain. Concerning the proposed application, an orthosis embedded with a surface electromyography (sEMG) measurement system was used to monitor the electrical activity of the forearm muscles during movement. This method was developed for the monitoring during rehabilitation. The proposed method is general, can be applied to any low frequency signal processing, and was built with wavelet algorithms from the WaveLab 850 library of the Stanford University (USA).

AB - This paper deals with the noise detection of discrete sEMG signals using wavelets. More specifically, it compares the usefullness of the Haars and Daubechies wavelets for the denoising and compression of the digitalized biosignal. The work is based upon the Discrete Wavelet Transform (DWT) version of Wavelet Package Transform (WPT). A denoising algorithm is proposed to detect unavoidable measured noise in the acquired data. With the help of a seminorm the noise of a sequence is defined. Using this norm it is possible to rearrange the wavelet basis, which can illuminate the differences between the coherent and incoherent parts of the sequence, where incoherent refers to the part of the signal that has either no information or contradictory information. In effect, the procedure looks for the subspace characterised either by small components or by opposing components in the wavelet domain. Concerning the proposed application, an orthosis embedded with a surface electromyography (sEMG) measurement system was used to monitor the electrical activity of the forearm muscles during movement. This method was developed for the monitoring during rehabilitation. The proposed method is general, can be applied to any low frequency signal processing, and was built with wavelet algorithms from the WaveLab 850 library of the Stanford University (USA).

KW - Engineering

KW - Wavelet packet transform

KW - Wavelet analysis

KW - Noise detection

KW - Biosignal processing

KW - ARM Processor Platform

UR - http://www.scopus.com/inward/record.url?scp=84954183576&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/record.url?scp=84992523130&partnerID=8YFLogxK

U2 - 10.1016/j.ifacol.2015.07.047

DO - 10.1016/j.ifacol.2015.07.047

M3 - Conference article in journal

VL - 48

SP - 278

EP - 283

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

SN - 2405-8971

IS - 4

T2 - 13th IFAC and IEEE Conference on Programmable Devices and Embedded Systems - PDES 2015

Y2 - 13 May 2015 through 15 May 2015

ER -