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Secondary measures of regularity from an entropy profile in detecting Arrhythmia
conference contribution
posted on 2017-07-01, 00:00 authored by Radhagayathri Krishnavilas Udhayakumar, Chandan KarmakarChandan Karmakar, Marimuthu PalaniswamiThe most recently introduced concept of a `complete entropy profile' is a non-parametric (with regard to tolerance r) approach of entropy estimation. Given a signal, on generating its complete entropy profile, numerous secondary measures of regularity can be derived from the same. These profile based measures are seen to outperform the traditional ApEn statistic (evaluated at a single r) in estimating signal regularity. In this paper, we compare the performance of ApEn (evaluated at an r = 0.15 * SD of signal and an m = 2) with that of profile based measures such as MaxApEn, TotalApEn, AvgApEn, SDApEn, kurtApEn and skewApEn, in detecting `Arrhythmic' RR interval signals from `Normal' RR interval signals. Results indisputably prove the superiority of AvgApEn (AUC > 0.9 at data lengths N ≥ 200) and MaxApEn (AUC > 0.75 at all data lengths) as regularity statistics in detecting Arrhythmia, above all the other measures used.
History
Event
IEEE Engineering in Medicine and Biology Society EMBC. Annual International Conference (39th : 2017 : Seogwipo, South Korea)Volume
2017Pagination
3485 - 3488Publisher
IEEELocation
Jeju Island, KoreaPlace of publication
Piscataway, N.J.Publisher DOI
Start date
2017-07-11End date
2017-07-15ISSN
1557-170XLanguage
engPublication classification
E Conference publication; E1 Full written paper - refereedCopyright notice
2017, IEEETitle of proceedings
EMBC 2017 : Proceedings of the 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)Usage metrics
Keywords
Arrhythmias, CardiacBiometryEntropyHumansScience & TechnologyLife Sciences & BiomedicineTechnologyBiophysicsEngineering, BiomedicalEngineeringApproximate entropyEntropy profileAutomatic selection of r thresholdNon-parametric entropy estimationArrhythmiaBiomedical signal analysisSAMPLE ENTROPYCOMPLEXITYSERIESAPENArtificial Intelligence and Image Processing
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