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Article

Statistical Evaluation of Transformation Methods Accuracy on Derived Pathological Vectorcardiographic Leads


. 2022 Apr 13;10:1900208.


doi: 10.1109/JTEHM.2022.3167009.


eCollection 2022.

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Jaroslav Vondrak et al.


IEEE J Transl Eng Health Med.


.

Abstract

Objective: Vectorcardiography (VCG) as an alternative form of ECG provides important spatial information about the electrical activity of the heart. It achieves higher sensitivity in the detection of some pathologies such as myocardial infarction, ischemia and hypertrophy. However, vectorcardiography is not commonly measured in clinical practice, and for this reason mathematical transformations have been developed to obtain derived VCG leads, which in application in current systems and subsequent analysis can contribute to early diagnosis and obtaining other useful information about the electrical activity of the heart. Methods and procedures: The most frequently used transformation methods are compared, namely the Kors regression method, the Inverse Dower transformation, QLSV and the Quasi-orthogonal transformation. These transformation methods were used on 30 randomly selected records with a diagnosis of myocardial infarction from the Physikalisch-Technische Bundesanstalt (PTB) database and their accuracy was evaluated based on the calculation of the mean square error (MSE). MSE was subjected to statistical evaluation at a significance level of 0.05. Results: Based on statistical testing using the nonparametric multiselective Kruskall-Wallis test and subsequent post-hoc analysis using the Dunn method, the Kors regression as a whole method achieved the most accurate transformation. Conclusion: The results of statistical analysis provide an evaluation of the accuracy of several transformation methods for deriving orthogonal leads, for possible application in measuring and evaluation systems, which may contribute to the correct choice of method for subsequent analysis of electrical activity of the heart at orthogonal leads to predict various diseases.


Keywords:

Transformation methods; statistical evaluation; transformation matrix; vectorcardiography.

Figures



FIGURE 1.

Location of electrodes in Frank lead system .


FIGURE 2.


FIGURE 2.

Examples of transformation methods used on a 12-lead ECG from a randomly selected record formula image with a diagnosis of myocardial infarction. The blue curve indicates the VCG measured by the Frank lead system and the red curve indicates the transformed curve.

FIGURE 3.


FIGURE 3.

Filtration of baseline wandering from a randomly selected record formula image (lead Z) with a diagnosis of myocardial infarction.

FIGURE 4.


FIGURE 4.

MSE for tested transformation methods in individual leads.


FIGURE 5.


FIGURE 5.

Gaussian curve with histograms of the tested methods.


FIGURE 6.


FIGURE 6.

Graphical representation of post-hoc analysis for individual leads.

References

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      PubMed

Grant support

This work was supported by the ‘Biomedical Engineering systems XVII’ under Project SV4500 × 21/2101 and Project SP2021/112.



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