Publication:
Quantifying respiration effects on cardiac vibrations using teager energy operator and gradient boosted trees

dc.contributor.departmentDepartment of Electrical and Electronics Engineering
dc.contributor.kuauthorGürsoy, Beren Semiz
dc.contributor.kuauthorİmirzalıoğlu, Mine
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.date.accessioned2024-11-10T00:06:34Z
dc.date.issued2022
dc.description.abstractThis work proposes a novel beat scoring system for quantifying the effects of exhalation and inhalation on the seismocardiogram (SCG) signals in rest and physiologically modulated conditions. Data from 19 subjects during rest, listening to classical music and recovery states were used. First, the SCG and electrocardiogram (ECG) signals were segmented into exhalation and inhalation phases using the respiration signal; and a representative SCG beat for each exhale and inhale phase was constructed using the ECG R-peak locations. Second, the significant differences across the exhalation- and inhalation-induced SCG beats were detected and extracted using the Teager- Kaiser energy operator. Finally, a gradient-based beat scoring system was developed using extreme gradient boosted trees and monotonic mapping. For the rest, classical music and recovery sessions, the area under the receiver operating characteristic curve was found to be 0.978, 0.874, 0.985, respectively. On the other hand, the kernel density estimation distributions of the inhalation and exhalation scores had an overlap of 14.2%, 41.2%, 10.6%, respectively. Overall, our results show that different physiological modulations directly change the effect of respiration on the SCG morphology, thus standardization across the beats should be studied for achieving more reliable and accurate investigation of cardiovascular parameters. Clinical relevance - Such a system can potentially allow for more informed and clinically useful SCG analysis by providing valuable insights regarding the intra-recording variability caused by the respiratory system.
dc.description.indexedbyScopus
dc.description.indexedbyPubMed
dc.description.openaccessYES
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuN/A
dc.description.volume2022-July
dc.identifier.doi10.1109/EMBC48229.2022.9871636
dc.identifier.isbn9781-7281-2782-8
dc.identifier.issn1557-170X
dc.identifier.scopus2-s2.0-85138127473
dc.identifier.urihttps://doi.org/10.1109/EMBC48229.2022.9871636
dc.identifier.urihttps://hdl.handle.net/20.500.14288/16637
dc.keywordsElectrocardiograms
dc.keywordsPhysiological models
dc.keywordsRespiratory system
dc.keywordsClassical musics
dc.keywordsCondition
dc.keywordsElectrocardiogram signal
dc.keywordsEnergy gradients
dc.keywordsEnergy operators
dc.keywordsGradient based
dc.keywordsRespiration signals
dc.keywordsScoring systems
dc.keywordsSeismocardiogram
dc.keywordsTeager energy operators
dc.keywordsForestry
dc.keywordsBreathing
dc.keywordsHeart
dc.keywordsHeart rate
dc.keywordsHuman
dc.keywordsPhysiology
dc.keywordsTree
dc.keywordsVibration
dc.keywordsHumans
dc.keywordsRespiration
dc.keywordsTrees
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartofProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
dc.subjectBallistocardiography
dc.subjectBreathing rate
dc.subjectSensor
dc.titleQuantifying respiration effects on cardiac vibrations using teager energy operator and gradient boosted trees
dc.typeConference Proceeding
dspace.entity.typePublication
local.contributor.kuauthorGürsoy, Beren Semiz
local.contributor.kuauthorİmirzalıoğlu, Mine
local.publication.orgunit1College of Engineering
local.publication.orgunit2Department of Electrical and Electronics Engineering
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relation.isOrgUnitOfPublication.latestForDiscovery21598063-a7c5-420d-91ba-0cc9b2db0ea0
relation.isParentOrgUnitOfPublication8e756b23-2d4a-4ce8-b1b3-62c794a8c164
relation.isParentOrgUnitOfPublication.latestForDiscovery8e756b23-2d4a-4ce8-b1b3-62c794a8c164

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