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A point process local likelihood algorithm for robust and automated heart beat detection and correction

Citi, L and Brown, EN and Barbieri, R (2011) A point process local likelihood algorithm for robust and automated heart beat detection and correction. In: UNSPECIFIED, ? - ?.

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Abstract

Robust and automated classification and correction of ECG-derived heart beats are a necessary prerequisite for an accurate real-time estimation of measures of heart rate variability and cardiovascular control. In particular, the low quality of the signal, as well as the presence of recurring arrhythmic events, may significantly affect estimation accuracy. We here present a novel point process based method for a real time R-R interval error detection and correction. Results of detection analysis over data from the benchmark MIT-BIH arrhythmia database demonstrate that the proposed algorithm achieves 99.97% accuracy (98.23% sensitivity, 99.98% specificity and 95.69% positive predictive value), outperforming state-of-the-art algorithms. Further results on simulated data demonstrate the efficacy of the detection and correction method. © 2011 CCAL.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: Computing in Cardiology
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > R Medicine (General)
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 04 Apr 2014 14:48
Last Modified: 17 Aug 2017 17:53
URI: http://repository.essex.ac.uk/id/eprint/8802

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