Acar, B.Köymen, Hayrettin2016-02-082016-02-081999-030018-9294http://hdl.handle.net/11693/25263An orthogonalization method to eliminate unwanted signal components in standard 12-lead exercise electrocardiograms (ECG's) is presented in this work. A singular-value-decomposition-based algorithm is proposed to decompose the signal into two time-orthogonal subspaces; one containing the ECG and the other containing artifacts like baseline wander and electromyogram. The method makes use of redundancy in 12-lead ECG. The same method is also tested for reconstruction of a completely lost channel. The online implementation of the method is given. It is observed that the first two decomposed channels with highest energy are sufficient to reconstruct the ST-segment and J- point. The dimension of the signal space, on the other hand, does not exceed three. Data from 23 patients, with duration ranging from 9 to 21 min, are used.An orthogonalization method to eliminate unwanted signal components in standard 12-lead exercise electrocardiograms (ECG's) is presented in this work. A singular-value-decomposition-based algorithm is proposed to decompose the signal into two time-orthogonal subspaces; one containing the ECG and the other containing artifacts like baseline wander and electromyogram. The method makes use of redundancy in 12-lead ECG. The same method is also tested for reconstruction of a completely lost channel. The online implementation of the method is given. It is observed that the first two decomposed channels with highest energy are sufficient to reconstruct the ST-segment and J-point. The dimension of the signal space, on the other hand, does not exceed three. Data from 23 patients, with duration ranging from 9 to 21 min, are used.EnglishElectromyogram (EMG)Exercise electrocardiogram (ECG)Online orthogonalizationSignal enhancementSingular value decomposition (SVD)AlgorithmsElectromyographySignal filtering and predictionSignal reconstructionSignal orthogonalizationElectrocardiographyElectrocardiographyExercise TestMicrocomputersArticle10.1109/10.748984