Please use this identifier to cite or link to this item: https://doi.org/10.1109/IEMBS.2011.6091365
DC FieldValue
dc.titleA computationally efficient QRS detection algorithm for wearable ECG sensors
dc.contributor.authorWang, Y.
dc.contributor.authorDeepu, C.J.
dc.contributor.authorLian, Y.
dc.date.accessioned2014-06-19T02:52:52Z
dc.date.available2014-06-19T02:52:52Z
dc.date.issued2011
dc.identifier.citationWang, Y., Deepu, C.J., Lian, Y. (2011). A computationally efficient QRS detection algorithm for wearable ECG sensors. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS : 5641-5644. ScholarBank@NUS Repository. https://doi.org/10.1109/IEMBS.2011.6091365
dc.identifier.isbn9781424441211
dc.identifier.issn1557170X
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/68757
dc.description.abstractIn this paper we present a novel Dual-Slope QRS detection algorithm with low computational complexity, suitable for wearable ECG devices. The Dual-Slope algorithm calculates the slopes on both sides of a peak in the ECG signal; And based on these slopes, three criterions are developed for simultaneously checking 1)Steepness 2)Shape and 3)Height of the signal, to locate the QRS complex. The algorithm, evaluated against MIT/BIH Arrhythmia Database, achieves a very high detection rate of 99.45%, a sensitivity of 99.82% and a positive prediction of 99.63%. © 2011 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/IEMBS.2011.6091365
dc.sourceScopus
dc.subjectElectrocardiogram
dc.subjectlow complexity
dc.subjectQRS detection
dc.subjectwearable sensors
dc.typeConference Paper
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1109/IEMBS.2011.6091365
dc.description.sourcetitleProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
dc.description.page5641-5644
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Staff Publications
Elements

Show simple item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
2011-a_computationally_efficient_qrs_detection-postprint.pdf729.43 kBAdobe PDF

OPEN

Post-printView/Download

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.