Accurate wearable heart rate monitoring during physical exercises using PPG

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dc.contributor.authorTemko, Andriy
dc.contributor.funderScience Foundation Irelanden
dc.date.accessioned2017-06-23T11:39:05Z
dc.date.available2017-06-23T11:39:05Z
dc.date.issued2017-03-01
dc.date.updated2017-06-23T11:21:54Z
dc.description.abstractObjective: The challenging task of heart rate (HR) estimation from the photoplethysmographic (PPG) signal, during intensive physical exercises is tackled in this paper. Methods: The study presents a detailed analysis of a novel algorithm (WFPV) that exploits a Wiener filter to attenuate the motion artifacts, a phase vocoder to refine the HR estimate and user-adaptive postprocessing to track the subject physiology. Additionally, an offline version of the HR estimation algorithm that uses Viterbi decoding is designed for scenarios that do not require online HR monitoring (WFPV+VD). The performance of the HR estimation systems is rigorously compared with existing algorithms on the publically available database of 23 PPG recordings. Results: On the whole dataset of 23 PPG recordings, the algorithms result in average absolute errors of 1.97 and 1.37 BPM in the online and offline modes, respectively. On the test dataset of 10 PPG recordings which were most corrupted with motion artifacts, WFPV has an error of 2.95 BPM on its own and 2.32 BPM in an ensemble with 2 existing algorithms. Conclusion: The error rate is significantly reduced when compared with the state-of-the art PPG-based HR estimation methods. Significance: The proposed system is shown to be accurate in the presence of strong motion artifacts and in contrast to existing alternatives has very few free parameters to tune. The algorithm has a low computational cost and can be used for fitness tracking and health monitoring in wearable devices. The Matlab implementation of the algorithm is provided online.en
dc.description.sponsorshipScience Foundation Ireland (SFI Research Centre Award (12/RC/2272))en
dc.description.statusPeer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationTemko, A. (2017) 'Accurate Wearable Heart Rate Monitoring During Physical Exercises Using PPG', IEEE Transactions on Biomedical Engineering, 64(9), pp. 2016-2024. doi: 10.1109/TBME.2017.2676243en
dc.identifier.doi10.1109/TBME.2017.2676243
dc.identifier.endpage2024
dc.identifier.issn0018-9294
dc.identifier.issued9
dc.identifier.journaltitleIEEE Transactions On Biomedical Engineeringen
dc.identifier.startpage2016
dc.identifier.urihttps://hdl.handle.net/10468/4185
dc.identifier.volume64
dc.language.isoenen
dc.publisherIEEEen
dc.rights© 2017, IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en
dc.subjectAccelerometersen
dc.subjectAlgorithm design and analysisen
dc.subjectEstimationen
dc.subjectHeart rateen
dc.subjectMonitoringen
dc.subjectVocodersen
dc.subjectWiener filtersen
dc.subjectPhotoplethysmographicen
dc.subjectViterbi decodingen
dc.subjectWiener filteren
dc.subjectPhase vocoderen
dc.subjectSpectrum estimationen
dc.titleAccurate wearable heart rate monitoring during physical exercises using PPGen
dc.typeArticle (peer-reviewed)en
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