Development of a Frequent Exchange Coordinate Algorithm for Detection of Precordial Electrode Exchange during ECG based on Error and Correlation Parameters

Edward Carello Figueroa Tejada; Carlos Esteban Mamani Huisa; Erasmo Sulla Espinoza; Jorge Eusebio Rendulich Talavera

doi:10.17488/RMIB.45.3.7

Authors

Edward Carello Figueroa Tejada Universidad Nacional de San Agustín de Arequipa, Perú https://orcid.org/0000-0001-6258-9322
Carlos Esteban Mamani Huisa Universidad Nacional de San Agustín de Arequipa, Perú
Erasmo Sulla Espinoza Universidad Nacional de San Agustín de Arequipa, Perú https://orcid.org/0000-0002-1223-1223
Jorge Eusebio Rendulich Talavera Universidad Nacional de San Agustín de Arequipa, Perú https://orcid.org/0000-0003-1302-547X

DOI:

https://doi.org/10.17488/RMIB.45.3.7

Keywords:

12-lead ECG, correlation, error estimators, electrode exchange

Abstract

In order to develop a method for detecting precordial electrode exchange, a frequent exchange coordinate (FEC) algorithm was implemented, that identified the minimum correlation points necessary to detect a specific electrode exchange, and its performance was tested with error estimators (mean square error and percent mean square difference). Validation of the algorithm was performed using the k-fold cross-validation technique on the PTB, Chapman University and Shaoxing Hospital, PTB XL, and Georgia 12-lead ECG Challenge databases. The results indicate averages of Se= 99.16 % and Sp= 99.38 % (MSE), Se= 95.38 % and Sp= 99.47 % (PRD), Se= 98.44 % and Sp= 99.49 % (Pearson), Se= 98.45 % and Sp= 99.48 % (modified Pearson), Se= 95.39 % and Sp= 99.81 % (Bray Curtis), Se= 80.00 % and Sp= 97.84 % (correlation sign). MSE presents a significant improvement in execution time (61.49µs N=1000), representing, on average, 44.99 % of the execution time for Pearson correlation. The frequent exchange coordinates algorithm was then validated using signal analysis with the mean square error (MSE), representing a good alternative to detect electrode exchange in real time, easy to implement, and low computational cost.

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