Period estimation of an almost periodic signal using persistent homology with application to respiratory rate measurement

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buir.contributor.authorÇetin, A. Enis
buir.contributor.orcidÇetin, A. Enis|0000-0002-3449-1958
dc.citation.epage962en_US
dc.citation.issueNumber7en_US
dc.citation.spage958en_US
dc.citation.volumeNumber24en_US
dc.contributor.authorErden, F.en_US
dc.contributor.authorÇetin, A. Enisen_US
dc.date.accessioned2018-04-12T11:45:43Z
dc.date.available2018-04-12T11:45:43Z
dc.date.issued2017en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.description.abstractTime-frequency techniques have difficulties in yielding efficient online algorithms for almost periodic signals. We describe a new topological method to find the period of signals that have an almost periodic waveform. Proposed method is applied to signals received from a pyro-electric infrared sensor array for the online estimation of the respiratory rate (RR) of a person. Timevarying analog signals captured from the sensors exhibit an almost periodic behavior due to repetitive nature of breathing activity. Sensor signals are transformed into two-dimensional point clouds with a technique that allows preserving the period information. Features, which represent the harmonic structures in the sensor signals, are detected by applying persistent homology and the RR is estimated based on the persistence barcode of the first Betti number. Experiments have been carried out to show that our method makes reliable estimates of the RR.en_US
dc.identifier.doi10.1109/LSP.2017.2699924en_US
dc.identifier.issn1070-9908
dc.identifier.urihttp://hdl.handle.net/11693/37615
dc.language.isoEnglishen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/LSP.2017.2699924en_US
dc.source.titleIEEE Signal Processing Lettersen_US
dc.subjectPeriodicityen_US
dc.subjectPersistent homologyen_US
dc.subjectPyro-electric infrared (PIR) sensoren_US
dc.subjectRespiratory rate (RR)en_US
dc.subjectTopological data analysisen_US
dc.titlePeriod estimation of an almost periodic signal using persistent homology with application to respiratory rate measurementen_US
dc.typeArticleen_US
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