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dc.contributor.authorMorelli, D
dc.contributor.authorBartoloni, L
dc.contributor.authorColombo, M
dc.contributor.authorPlans, D
dc.contributor.authorClifton, DA
dc.date.accessioned2019-01-25T14:45:06Z
dc.date.issued2018-05-07
dc.description.abstractWearable physiological monitors are becoming increasingly commonplace in the consumer domain, but in literature there exists no substantive studies of their performance when measuring the physiology of ambulatory patients. In this Letter, the authors investigate the reliability of the heart-rate (HR) sensor in an exemplar 'wearable' wrist-worn monitoring system (the Microsoft Band 2); their experiments quantify the propagation of error from (i) the photoplethysmogram (PPG) acquired by pulse oximetry, to (ii) estimation of HR, and (iii) subsequent calculation of HR variability (HRV) features. Their experiments confirm that motion artefacts account for the majority of this error, and show that the unreliable portions of HR data can be removed, using the accelerometer sensor from the wearable device. The experiments further show that acquired signals contain noise with substantial energy in the high-frequency band, and that this contributes to subsequent variability in standard HRV features often used in clinical practice. The authors finally show that the conventional use of long-duration windows of data is not needed to perform accurate estimation of time-domain HRV features.en_GB
dc.identifier.citationVol. 5, pp. 59 - 64en_GB
dc.identifier.doi10.1049/htl.2017.0039
dc.identifier.urihttp://hdl.handle.net/10871/35591
dc.language.isoenen_GB
dc.publisherInstitution of Engineering and Technology (IET)en_GB
dc.rights© The Author(s) 2018. This is an open access article published by the IET under the Creative Commons Attribution -NonCommercial License (http:// creativecommons.org/licenses/by-nc/3.0/)en_GB
dc.subjecttime-domain analysis
dc.subjectpatient monitoring
dc.subjectbiomedical equipment
dc.subjectfeature extraction
dc.subjectbody sensor networks
dc.subjectphotoplethysmography
dc.subjectoximetry
dc.subjectaccelerometers
dc.subjectacceleration measurement
dc.subjectsignal denoising
dc.subjectmedical signal processing
dc.titleProfiling the propagation of error from PPG to HRV features in a wearable physiological-monitoring deviceen_GB
dc.typeArticleen_GB
dc.date.available2019-01-25T14:45:06Z
dc.descriptionThis is the final version. Available on open access from IET via the DOI in this recorden_GB
dc.identifier.journalHealthcare Technology Lettersen_GB
dc.rights.urihttp://creativecommons.org/licenses/by-nc/3.0/en_GB
dcterms.dateAccepted2017-07-19
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2017-07-19
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2019-01-25T14:43:13Z
refterms.versionFCDVoR
refterms.dateFOA2019-01-25T14:45:09Z
refterms.panelCen_GB
refterms.depositExceptionpublishedGoldOA


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© The Author(s) 2018. This is an open access article published by the IET under the
Creative Commons Attribution -NonCommercial License (http://
creativecommons.org/licenses/by-nc/3.0/)
Except where otherwise noted, this item's licence is described as © The Author(s) 2018. This is an open access article published by the IET under the Creative Commons Attribution -NonCommercial License (http:// creativecommons.org/licenses/by-nc/3.0/)