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P- and T-wave delineation in ECG signals using parametric mixture Gaussian and dynamic programming

Rao MV, A and Gupta, P and Ghosh, PK (2019) P- and T-wave delineation in ECG signals using parametric mixture Gaussian and dynamic programming. In: Biomedical Signal Processing and Control, 51 . pp. 328-337.

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Official URL: https://dx.doi.org/10.1016/j.bspc.2019.03.001

Abstract

Detection and tracking of the P- and T-waves are important issues in the analysis and interpretation of the ECG signals. This paper addresses the problem by using two mixture Gaussian function and the Dynamic programming. A key feature of the proposed algorithm is that it allows to incorporate the prior knowledge about the P/T wave location variations and robustness to errors in QRS detection. The proposed algorithm is evaluated on the annotated QT-database and compared against the algorithms based on differential evolution optimization strategy (DEOS) and generating blocks of interest (GBI). The experiments show that the proposed method determines the P- and T-peak locations with a root mean square error of 0.085 s and 0.091 s respectively. Both these values are better than the corresponding values from DEOS and GBI. Similarly, the proposed algorithm achieves a sensitivity of 96.13 and predictivity of 97.70. While the predictivity is higher than both DEOS and GBI, the sensitivity is on par with GBOI and higher than that of DEOS.

Item Type: Journal Article
Publication: Biomedical Signal Processing and Control
Publisher: Elsevier Ltd
Additional Information: copyright for this article belongs to Elsevier Ltd
Keywords: Electrocardiography; Evolutionary algorithms; Mean square error; Mixtures, Detection and tracking; Differential evolution optimizations; Gaussian functions; Location variation; Predictivity; Prior knowledge; QRS detection; Root mean square errors, Dynamic programming, article; controlled study; diagnostic test accuracy study; error; P wave; T wave
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 09 Apr 2019 05:28
Last Modified: 09 Apr 2019 05:28
URI: http://eprints.iisc.ac.in/id/eprint/62060

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