Synthesis of 12-Lead ECG from a Reduced Lead Set using Singular Value Decomposition

This paper presents synthesis of 12-lead Electrocardiogram (ECG) from a reduced set of leads. A patient-specific 12-lead ECG is trained using the Singular Value Decomposition (SVD) for minimum of three beat periods. Then, in the testing stage, different reduced lead sets comprising of three leads are used to reconstruct all other leads. The singular value matrix of the reduced 3-lead data is transformed to a higher dimension using a transform matrix. For evaluation purpose, the proposed method is applied to a publicly available database. It contains number of 12-lead ECG recordings with different cardiac patients' data. The proposed method performs well for reconstruction of precordial leads in case of myocardial infarction. The percent correlation exceeds 97% for most of the precordial leads. After reconstruction of 12-lead ECG data, the performance of the method is measured using three measures namely percent correlation, PRD and WEDD between the original and the synthesized data.