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Conference Paper: Study on adaptive noise canceller based on fixed-point algorithm for real-time somatosensory evoked potential monitoring

TitleStudy on adaptive noise canceller based on fixed-point algorithm for real-time somatosensory evoked potential monitoring
Authors
KeywordsAdaptive Noise Canceller
Fixed-Point Algorithm
Somsatosensory Evoked Potential
Step-Size Parameter
Issue Date2008
Citation
2Nd International Conference On Bioinformatics And Biomedical Engineering, Icbbe 2008, 2008, p. 2213-2216 How to Cite?
AbstractThe objective of this study was to analyze the performance of fixed-point adaptive noise canceller (ANC) for SEP measurement, as well as compare with the outputs of floating-point ANC at 16 bits word-length. ANC technique has been reported powerful to improve signal to noise ratio (SNR) of somsatosensory evoked potential (SEP). For the sake of real-time monitoring of intraoperative SEP, both fixed-point and floating-point algorithms can be applied to Field Programmable Gate Array (FPGA) design. However, the ability of fixed-point ANC to improve the SNR of SEP is still dubious. In simulation, SEP signals from 7 patients were included. The results showed that outputs of fixed-point ANC had higher distortion index (DI) from real SEP signals than that of floating-point ANC at the same step-size parameter (μ), and optimal range of μ value was different in fixed-point algorithm from floating-point algorithm at the same DI. However, the two algorithms had very similar DI trend curves when μ value and trail number varied in a certain range, the fixed-point ANC can extract SEP from raw signals as effectively as floating-point ANC, compared with ensemble averaging SEP of 300 raw SEP signals. It would be helpful to design fixed-point ANC based on FPGA for real-time monitoring of intraoperative SEP. © 2008 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/173407
References

 

DC FieldValueLanguage
dc.contributor.authorCui, Hen_US
dc.contributor.authorShen, Cen_US
dc.contributor.authorXie, Xen_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.issued2008en_US
dc.identifier.citation2Nd International Conference On Bioinformatics And Biomedical Engineering, Icbbe 2008, 2008, p. 2213-2216en_US
dc.identifier.urihttp://hdl.handle.net/10722/173407-
dc.description.abstractThe objective of this study was to analyze the performance of fixed-point adaptive noise canceller (ANC) for SEP measurement, as well as compare with the outputs of floating-point ANC at 16 bits word-length. ANC technique has been reported powerful to improve signal to noise ratio (SNR) of somsatosensory evoked potential (SEP). For the sake of real-time monitoring of intraoperative SEP, both fixed-point and floating-point algorithms can be applied to Field Programmable Gate Array (FPGA) design. However, the ability of fixed-point ANC to improve the SNR of SEP is still dubious. In simulation, SEP signals from 7 patients were included. The results showed that outputs of fixed-point ANC had higher distortion index (DI) from real SEP signals than that of floating-point ANC at the same step-size parameter (μ), and optimal range of μ value was different in fixed-point algorithm from floating-point algorithm at the same DI. However, the two algorithms had very similar DI trend curves when μ value and trail number varied in a certain range, the fixed-point ANC can extract SEP from raw signals as effectively as floating-point ANC, compared with ensemble averaging SEP of 300 raw SEP signals. It would be helpful to design fixed-point ANC based on FPGA for real-time monitoring of intraoperative SEP. © 2008 IEEE.en_US
dc.languageengen_US
dc.relation.ispartof2nd International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2008en_US
dc.subjectAdaptive Noise Cancelleren_US
dc.subjectFixed-Point Algorithmen_US
dc.subjectSomsatosensory Evoked Potentialen_US
dc.subjectStep-Size Parameteren_US
dc.titleStudy on adaptive noise canceller based on fixed-point algorithm for real-time somatosensory evoked potential monitoringen_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/ICBBE.2008.884en_US
dc.identifier.scopuseid_2-s2.0-50949128322en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-50949128322&selection=ref&src=s&origin=recordpageen_US
dc.identifier.spage2213en_US
dc.identifier.epage2216en_US
dc.identifier.scopusauthoridCui, H=35745716900en_US
dc.identifier.scopusauthoridShen, C=23390267000en_US
dc.identifier.scopusauthoridXie, X=53870912800en_US
dc.identifier.scopusauthoridHu, Y=7407116091en_US
dc.identifier.scopusauthoridLuk, KDK=7201921573en_US

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