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Article: A novel method for nonstationary power spectral density estimation of cardiovascular pressure signals based on a Kalman filter with variable number of measurements

TitleA novel method for nonstationary power spectral density estimation of cardiovascular pressure signals based on a Kalman filter with variable number of measurements
Authors
Issue Date2008
PublisherSpringer Verlag. The Journal's web site is located at http://www.springer.com/sgw/cda/frontpage/0,11855,4-40109-70-67951916-0,00.html?changeHeader=true
Citation
Medical And Biological Engineering And Computing, 2008, v. 46 n. 8, p. 789-797 How to Cite?
AbstractWe present a novel parametric power spectral density (PSD) estimation algorithm for nonstationary signals based on a Kalman filter with variable number of measurements (KFVNM). The nonstationary signals under consideration are modeled as time-varying autoregressive (AR) processes. The proposed algorithm uses a block of measurements to estimate the time-varying AR coefficients and obtains high-resolution PSD estimates. The intersection of confidence intervals (ICI) rule is incorporated into the algorithm to generate a PSD with adaptive window size from a series of PSDs with different number of measurements. We report the results of a quantitative assessment study and show an illustrative example involving the application of the algorithm to intracranial pressure signals (ICP) from patients with traumatic brain injury (TBI). © International Federation for Medical and Biological Engineering 2008.
Persistent Identifierhttp://hdl.handle.net/10722/143332
ISSN
2015 Impact Factor: 1.797
2015 SCImago Journal Rankings: 0.798
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorZhang, ZGen_HK
dc.contributor.authorTsui, KMen_HK
dc.contributor.authorChan, SCen_HK
dc.contributor.authorLau, WYen_HK
dc.contributor.authorAboy, Men_HK
dc.date.accessioned2011-11-22T08:30:40Z-
dc.date.available2011-11-22T08:30:40Z-
dc.date.issued2008en_HK
dc.identifier.citationMedical And Biological Engineering And Computing, 2008, v. 46 n. 8, p. 789-797en_HK
dc.identifier.issn0140-0118en_HK
dc.identifier.urihttp://hdl.handle.net/10722/143332-
dc.description.abstractWe present a novel parametric power spectral density (PSD) estimation algorithm for nonstationary signals based on a Kalman filter with variable number of measurements (KFVNM). The nonstationary signals under consideration are modeled as time-varying autoregressive (AR) processes. The proposed algorithm uses a block of measurements to estimate the time-varying AR coefficients and obtains high-resolution PSD estimates. The intersection of confidence intervals (ICI) rule is incorporated into the algorithm to generate a PSD with adaptive window size from a series of PSDs with different number of measurements. We report the results of a quantitative assessment study and show an illustrative example involving the application of the algorithm to intracranial pressure signals (ICP) from patients with traumatic brain injury (TBI). © International Federation for Medical and Biological Engineering 2008.en_HK
dc.languageengen_US
dc.publisherSpringer Verlag. The Journal's web site is located at http://www.springer.com/sgw/cda/frontpage/0,11855,4-40109-70-67951916-0,00.html?changeHeader=trueen_HK
dc.relation.ispartofMedical and Biological Engineering and Computingen_HK
dc.subject.meshAlgorithmsen_HK
dc.subject.meshBlood Pressureen_HK
dc.subject.meshBrain Injuries - physiopathologyen_HK
dc.subject.meshDiagnosis, Computer-Assisted - methodsen_HK
dc.subject.meshHumansen_HK
dc.subject.meshIntracranial Pressureen_HK
dc.subject.meshMonitoring, Physiologic - methodsen_HK
dc.subject.meshSignal Processing, Computer-Assisteden_HK
dc.titleA novel method for nonstationary power spectral density estimation of cardiovascular pressure signals based on a Kalman filter with variable number of measurementsen_HK
dc.typeArticleen_HK
dc.identifier.emailTsui, KM:kmtsui@eee.hku.hken_HK
dc.identifier.emailChan, SC:scchan@eee.hku.hken_HK
dc.identifier.authorityTsui, KM=rp00181en_HK
dc.identifier.authorityChan, SC=rp00094en_HK
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1007/s11517-008-0351-xen_HK
dc.identifier.pmid18496723-
dc.identifier.scopuseid_2-s2.0-48849099077en_HK
dc.identifier.hkuros159399-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-48849099077&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume46en_HK
dc.identifier.issue8en_HK
dc.identifier.spage789en_HK
dc.identifier.epage797en_HK
dc.identifier.isiWOS:000258117900006-
dc.publisher.placeGermanyen_HK
dc.identifier.scopusauthoridZhang, ZG=8407277900en_HK
dc.identifier.scopusauthoridTsui, KM=7101671591en_HK
dc.identifier.scopusauthoridChan, SC=13310287100en_HK
dc.identifier.scopusauthoridLau, WY=13608386400en_HK
dc.identifier.scopusauthoridAboy, M=7003563574en_HK
dc.identifier.citeulike2918069-

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