DocumentCode
2086383
Title
Empirical mode decomposition as a tool to remove the function Electrical stimulation artifact from surface electromyograms: Preliminary investigation
Author
Pilkar, R.B. ; Yarossi, Mathew ; Forrest, G.
Author_Institution
Kessler Found., West Orange, NJ, USA
fYear
2012
fDate
Aug. 28 2012-Sept. 1 2012
Firstpage
1847
Lastpage
1850
Abstract
Rectification of surface EMGs during electrical stimulations (ES) is still a problem to be solved. The broad band frequency components of ES artifact overlap with the EMG spectrum, make this task challenging. In this study, we investigate the potential use of empirical mode decomposition (EMD) method to remove the stimulus artifact from surface EMGs collected during such applications. We hypothesize that the EMD algorithm provides a suitable platform for decomposing the EMG signal into physically meaningful intrinsic modes which can be used to isolate ES artifact. Basic EMD is tested on two signals - ES induced EMG and EMG of voluntary contractions added with simulated ES signal. The algorithm isolates the EMG from ES artifact with considerable success. Further, the EMD method along with the energy operator -TKEO gives even better representation of the EMG signal. However, some high frequency data was lost during reconstruction process. Hence, there is further need to investigate the relationship between the EMD parameters and stimulus artifact properties so that the algorithm can be optimized to reconstruct pure artifact free EMG signal with minimum lost of data.
Keywords
electromyography; medical signal processing; signal reconstruction; EMG signal decomposition; empirical mode decomposition; energy operator; functional electrical stimulation artifact; signal reconstruction; surface EMG; surface electromyogram; Data mining; Electrical stimulation; Electromyography; Muscles; Physiology; USA Councils; Adult; Algorithms; Artifacts; Electric Stimulation; Electromyography; Fourier Analysis; Humans; Image Processing, Computer-Assisted; Male; Muscle Contraction; Muscle, Skeletal; Signal Processing, Computer-Assisted; Surface Properties;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
Conference_Location
San Diego, CA
ISSN
1557-170X
Print_ISBN
978-1-4244-4119-8
Electronic_ISBN
1557-170X
Type
conf
DOI
10.1109/EMBC.2012.6346311
Filename
6346311
Link To Document