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Conference Paper: Adaptive signal enhancement of somatosensory evoked potentials based on least mean squares and Kalman filter: A comparative study

TitleAdaptive signal enhancement of somatosensory evoked potentials based on least mean squares and Kalman filter: A comparative study
Authors
KeywordsAdaptive signal enhancement
Ensemble averaging
Kalman filter
Least mean squares
Somatosensory evoked potential
Issue Date2009
Citation
2009 4Th International Ieee/Embs Conference On Neural Engineering, Ner '09, 2009, p. 738-741 How to Cite?
AbstractThis paper undertakes a comparative study of adaptive signal enhancers (ASE) of somatosensory evoked potentials (SEP) for spinal cord compression detection. We compare the ASE methods based on two adaptive filtering algorithms: the least mean squares (LMS) and Kalman filter (KF) in terms of their convergence rate, variability, and complexity. In addition, the two ASE methods are compared with the conventional ensemble averaging (EA) method for SEP extraction. Experimental results on a rat model show that the LMS-based and KF-based ASE methods have similar superior performance over the EA method and the two ASE methods also exhibit some slightly different properties during SEP extraction. ©2009 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/143323
References

 

DC FieldValueLanguage
dc.contributor.authorZhao, HSen_HK
dc.contributor.authorZhang, ZGen_HK
dc.contributor.authorLiu, HTen_HK
dc.contributor.authorLuk, KDKen_HK
dc.contributor.authorHu, Yen_HK
dc.date.accessioned2011-11-22T08:30:19Z-
dc.date.available2011-11-22T08:30:19Z-
dc.date.issued2009en_HK
dc.identifier.citation2009 4Th International Ieee/Embs Conference On Neural Engineering, Ner '09, 2009, p. 738-741en_US
dc.identifier.urihttp://hdl.handle.net/10722/143323-
dc.description.abstractThis paper undertakes a comparative study of adaptive signal enhancers (ASE) of somatosensory evoked potentials (SEP) for spinal cord compression detection. We compare the ASE methods based on two adaptive filtering algorithms: the least mean squares (LMS) and Kalman filter (KF) in terms of their convergence rate, variability, and complexity. In addition, the two ASE methods are compared with the conventional ensemble averaging (EA) method for SEP extraction. Experimental results on a rat model show that the LMS-based and KF-based ASE methods have similar superior performance over the EA method and the two ASE methods also exhibit some slightly different properties during SEP extraction. ©2009 IEEE.en_HK
dc.languageengen_US
dc.relation.ispartof2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09en_HK
dc.subjectAdaptive signal enhancementen_HK
dc.subjectEnsemble averagingen_HK
dc.subjectKalman filteren_HK
dc.subjectLeast mean squaresen_HK
dc.subjectSomatosensory evoked potentialen_HK
dc.titleAdaptive signal enhancement of somatosensory evoked potentials based on least mean squares and Kalman filter: A comparative studyen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailZhang, ZG:zgzhang@eee.hku.hken_HK
dc.identifier.emailLuk, KDK:hcm21000@hku.hken_HK
dc.identifier.emailHu, Y:yhud@hku.hken_HK
dc.identifier.authorityZhang, ZG=rp01565en_HK
dc.identifier.authorityLuk, KDK=rp00333en_HK
dc.identifier.authorityHu, Y=rp00432en_HK
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1109/NER.2009.5109402en_HK
dc.identifier.scopuseid_2-s2.0-70350234831en_HK
dc.identifier.hkuros159407-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-70350234831&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage738en_HK
dc.identifier.epage741en_HK
dc.identifier.scopusauthoridZhao, HS=35118331700en_HK
dc.identifier.scopusauthoridZhang, ZG=8597618700en_HK
dc.identifier.scopusauthoridLiu, HT=26643490700en_HK
dc.identifier.scopusauthoridLuk, KDK=7201921573en_HK
dc.identifier.scopusauthoridHu, Y=7407116091en_HK

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