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Conference Paper: ICA-based ECG removal from surface electromyography and its effect on low back pain assessment

TitleICA-based ECG removal from surface electromyography and its effect on low back pain assessment
Authors
KeywordsEcg Removal
Independent Component Analysis (Ica)
Low Back Pain
Rehabilitation
Surface Electromyography
Issue Date2007
Citation
Proceedings Of The 3Rd International Ieee Embs Conference On Neural Engineering, 2007, p. 646-649 How to Cite?
AbstractSurface electromyography (SEMG) has been used for muscle function examination in neuromuscular disorders. The utility of SEMG in Low Back Pain (LBP) assessment was questioned because of low sensitivity. Artifacts and noise contamination may distort the SEMG measurement in LBP assessment. The purposes of this study were to develop an ICA-based ECG removal method to obtain clean SEMG signal from back muscles, and to demonstrate the relative effect of ECG on back muscles SEMG parameters and their sensitivity on low back pain (LBP) assessment. This study compared surface EMG measurements on paraspinal muscles from 10 normal and 10 LBP patients during sitting and standing. The raw SEMG signal was processed by independent component analysis (ICA) to remove the ECG contamination. Then, median frequency (MF) of both raw and denoised paraspinal SEMG were calculated respectively. The MF of healthy and LBP groups before and after ECG removal were compared separately to evaluate the effect of ECG contamination. Also, difference between MF in subject with and without LBP were compared in raw and denoise condition to study the ECG effect on LBP assessment sensitivity. Significant MF increases (p<0.05) were founded after ECG noise removal in all tests. For LBP assessment, improvements in discriminative ability, in terms of parametric difference, were seen in MF parameter during sitting (mean difference between normal and patient increase from: Left: 8 to 45Hz; Right 11 to 53Hz) and standing (mean difference between normal and patient increase from: Left: -10 to 6Hz; Right 8 to 14Hz) respectively. ECG contaminations showed significantly influence on SEMG measurements in both normal and LBP patients. Our study has demonstrated the ability of the proposed ICA-based technique in ECG removal, which leads to an improvement in LBP assessment sensitivity. ©2007 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/173406
References

 

DC FieldValueLanguage
dc.contributor.authorMak, JNFen_US
dc.contributor.authorHu, Yen_US
dc.contributor.authorLuk, KDKen_US
dc.date.accessioned2012-10-30T06:30:53Z-
dc.date.available2012-10-30T06:30:53Z-
dc.date.issued2007en_US
dc.identifier.citationProceedings Of The 3Rd International Ieee Embs Conference On Neural Engineering, 2007, p. 646-649en_US
dc.identifier.urihttp://hdl.handle.net/10722/173406-
dc.description.abstractSurface electromyography (SEMG) has been used for muscle function examination in neuromuscular disorders. The utility of SEMG in Low Back Pain (LBP) assessment was questioned because of low sensitivity. Artifacts and noise contamination may distort the SEMG measurement in LBP assessment. The purposes of this study were to develop an ICA-based ECG removal method to obtain clean SEMG signal from back muscles, and to demonstrate the relative effect of ECG on back muscles SEMG parameters and their sensitivity on low back pain (LBP) assessment. This study compared surface EMG measurements on paraspinal muscles from 10 normal and 10 LBP patients during sitting and standing. The raw SEMG signal was processed by independent component analysis (ICA) to remove the ECG contamination. Then, median frequency (MF) of both raw and denoised paraspinal SEMG were calculated respectively. The MF of healthy and LBP groups before and after ECG removal were compared separately to evaluate the effect of ECG contamination. Also, difference between MF in subject with and without LBP were compared in raw and denoise condition to study the ECG effect on LBP assessment sensitivity. Significant MF increases (p<0.05) were founded after ECG noise removal in all tests. For LBP assessment, improvements in discriminative ability, in terms of parametric difference, were seen in MF parameter during sitting (mean difference between normal and patient increase from: Left: 8 to 45Hz; Right 11 to 53Hz) and standing (mean difference between normal and patient increase from: Left: -10 to 6Hz; Right 8 to 14Hz) respectively. ECG contaminations showed significantly influence on SEMG measurements in both normal and LBP patients. Our study has demonstrated the ability of the proposed ICA-based technique in ECG removal, which leads to an improvement in LBP assessment sensitivity. ©2007 IEEE.en_US
dc.languageengen_US
dc.relation.ispartofProceedings of the 3rd International IEEE EMBS Conference on Neural Engineeringen_US
dc.subjectEcg Removalen_US
dc.subjectIndependent Component Analysis (Ica)en_US
dc.subjectLow Back Painen_US
dc.subjectRehabilitationen_US
dc.subjectSurface Electromyographyen_US
dc.titleICA-based ECG removal from surface electromyography and its effect on low back pain assessmenten_US
dc.typeConference_Paperen_US
dc.identifier.emailHu, Y:yhud@hku.hken_US
dc.identifier.emailLuk, KDK:hcm21000@hku.hken_US
dc.identifier.authorityHu, Y=rp00432en_US
dc.identifier.authorityLuk, KDK=rp00333en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1109/CNE.2007.369756en_US
dc.identifier.scopuseid_2-s2.0-34548795881en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-34548795881&selection=ref&src=s&origin=recordpageen_US
dc.identifier.spage646en_US
dc.identifier.epage649en_US
dc.identifier.scopusauthoridMak, JNF=35980187600en_US
dc.identifier.scopusauthoridHu, Y=7407116091en_US
dc.identifier.scopusauthoridLuk, KDK=7201921573en_US

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