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Conference Paper: Applying independent component analysis on ECG cancellation technique for the surface recording of trunk electromyography

TitleApplying independent component analysis on ECG cancellation technique for the surface recording of trunk electromyography
Authors
KeywordsElectrocardiogram (Ecg)
Independent Component Analysis (Ica)
Noise Cancellation
Surface Electromyography (Semg)
Issue Date2005
Citation
The 27th Annual International Conference of the Engineering in Medicine and Biology Society (IEEE-EMBS 2005), Shanghai, China, 1-4 September 2005. In Conference Proceedings, 2005, p. 3647-3649 How to Cite?
AbstractSurface electromyography (sEMG) recorded from the trunk area may reflect underlying muscular function, and is the current standard for in vivo functional examination. However, sEMG of this area, including the low back musculature, usually encounters substantial interference from strong cardiac signals. It is therefore imperative to remove electrocardiogram (ECG) interference from sEMG data. This paper discusses a denoise method using independent component analysis (ICA) and a high-pass filter to effectively suppress the interference of ECG in sEMG recorded from trunk muscles. The performance of this technique was evaluated with simulation experiments. To compare the outcome of the ICA and filtering technique to the original sEMG signal, correlation coefficients in both time-domain waveform and frequency spectrum were computed. In addition, different filter bands were evaluated. The ICA ECG cancellation with a 30Hz high-pass filter showed higher mean correlation coefficients in the time domain (0.97±0.08) and in the frequency spectrum (0.99±0.06) than any other techniques. This suggests that the ICA ECG cancellation technique with a 30 Hz high-pass filter would be the most appropriate method to extract useful sEMG signals from trunk muscles. ©2005 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/173400
ISSN
2023 SCImago Journal Rankings: 0.340
References

 

DC FieldValueLanguage
dc.contributor.authorHu, Yen_US
dc.contributor.authorLi, XHen_US
dc.contributor.authorXie, XBen_US
dc.contributor.authorPang, LYen_US
dc.contributor.authorCao, Yen_US
dc.contributor.authorLuk, KDKen_US
dc.date.accessioned2012-10-30T06:30:51Z-
dc.date.available2012-10-30T06:30:51Z-
dc.date.issued2005en_US
dc.identifier.citationThe 27th Annual International Conference of the Engineering in Medicine and Biology Society (IEEE-EMBS 2005), Shanghai, China, 1-4 September 2005. In Conference Proceedings, 2005, p. 3647-3649en_US
dc.identifier.issn0589-1019en_US
dc.identifier.urihttp://hdl.handle.net/10722/173400-
dc.description.abstractSurface electromyography (sEMG) recorded from the trunk area may reflect underlying muscular function, and is the current standard for in vivo functional examination. However, sEMG of this area, including the low back musculature, usually encounters substantial interference from strong cardiac signals. It is therefore imperative to remove electrocardiogram (ECG) interference from sEMG data. This paper discusses a denoise method using independent component analysis (ICA) and a high-pass filter to effectively suppress the interference of ECG in sEMG recorded from trunk muscles. The performance of this technique was evaluated with simulation experiments. To compare the outcome of the ICA and filtering technique to the original sEMG signal, correlation coefficients in both time-domain waveform and frequency spectrum were computed. In addition, different filter bands were evaluated. The ICA ECG cancellation with a 30Hz high-pass filter showed higher mean correlation coefficients in the time domain (0.97±0.08) and in the frequency spectrum (0.99±0.06) than any other techniques. This suggests that the ICA ECG cancellation technique with a 30 Hz high-pass filter would be the most appropriate method to extract useful sEMG signals from trunk muscles. ©2005 IEEE.en_US
dc.languageengen_US
dc.relation.ispartofAlliance for Engineering in Medicine and Biology. Proceedings of the Annual Conferenceen_US
dc.subjectElectrocardiogram (Ecg)en_US
dc.subjectIndependent Component Analysis (Ica)en_US
dc.subjectNoise Cancellationen_US
dc.subjectSurface Electromyography (Semg)en_US
dc.titleApplying independent component analysis on ECG cancellation technique for the surface recording of trunk electromyographyen_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.scopuseid_2-s2.0-33846909543en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33846909543&selection=ref&src=s&origin=recordpageen_US
dc.identifier.spage3647en_US
dc.identifier.epage3649en_US
dc.publisher.placeUnited Statesen_US
dc.identifier.scopusauthoridHu, Y=7407116091en_US
dc.identifier.scopusauthoridLi, XH=53870484800en_US
dc.identifier.scopusauthoridXie, XB=53870912800en_US
dc.identifier.scopusauthoridPang, LY=53870603300en_US
dc.identifier.scopusauthoridCao, Y=13104339000en_US
dc.identifier.scopusauthoridLuk, KDK=7201921573en_US
dc.customcontrol.immutablesml 170512 amended-
dc.identifier.issnl0589-1019-

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