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Body surface lead reduction algorithm and its use in inverse problem of electrocardiography
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Date
2015
Author
Gharbalchi No, Fourough
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Determining electrical activity of the heart in a non-invasive way is one of the main issues in electrocardiography (ECG). Although several cardiac abnormalities can be diagnosed by the standard 12-lead ECG, many others are not detectable by this fixed lead configuration. One alternative to compensate for the imperfection of standard 12-lead ECG in detecting many of the most informative signals is Body Surface Potential Mapping (BSPM), which measures ECG signals from a dense array of electrodes (32-256 electrodes) over the body surface. However, besides having no standard lead-set configuration, this method suffers from the need for a large number of leads to perform with an acceptable accuracy. Therefore, despite having the potential to be used in clinical applications, BSPM has not been a practically accepted method. This study aims to propose a specific lead-set configuration, whose acquired data is sufficient to be used in inverse problem of ECG to reconstruct epicardial potentials with high accuracy. Towards this end, in our study, a lead reduction algorithm is proposed and implemented. As a result of applying the lead reduction algorithm on 23 different data-sets related to 23 different stimulation sites on the surface of the heart, 23 exclusive lead-set configurations corresponding to these 23 data-sets are obtained. Then, by selecting the most repeated leads, two common lead-set configurations, one consisting 64 and the other consisting of 32 leads, are obtained. To assess the performance of the proposed common lead-set configurations, inverse problem of ECG is solved using the data obtained by these lead-sets and the results are compared to those of exclusively optimal lead-sets, and the original complete lead-set. Mean and standard deviation values of Correlation Coefficient (CC) values obtained at each time instant between the true epicardial potentials and the inverse solutions are used to compare the results. By examining these mean and standard deviation of CC values, it has been observed that, instead of large number of leads, small number of leads optimally located on the surface of the torso would be sufficient to reconstruct the epicardial potentials accurately. Additionally, inverse problem of ECG is solved using four different regularization algorithms, namely, Tikhonov Regularization, Truncated Total Least Squares (TTLS), Lanczos Truncated Total Least Squares (LTTLS), and Lanczos Least Squares QR (LLSQR), using data from the original complete lead-set, exclusively optimal and common lead-sets (32 and leads). Mean and standard deviation values of Correlation Coefficient (CC) for these inverse solutions are calculated and compared for three different data-sets. It is observed that LTTLS method reconstructs the epicardial potentials better than the TTLS and LLSQR methods.
Subject Keywords
Electrocardiography.
,
Electrodiagnosis.
,
Least squares.
,
Mathematical statistics.
URI
http://etd.lib.metu.edu.tr/upload/12618376/index.pdf
https://hdl.handle.net/11511/24347
Collections
Graduate School of Natural and Applied Sciences, Thesis
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F. Gharbalchi No, “Body surface lead reduction algorithm and its use in inverse problem of electrocardiography,” M.S. - Master of Science, Middle East Technical University, 2015.
