Quantifying Clinical Information in MECG Using Sample and Channel Convolution Matrices

In this paper, a novel distortion measure is presented for quantifying loss of clinical information in multichannel electrocardiogram (MECG) signals. The proposed measure (SCPRD) is defined as the sum of percentage root mean square difference between magnitudes of convolution response of original and processed MECG signals. The convolution operation is performed with the help of proposed sample and channel convolution matrices. The SCPRD measure is compared with average wavelet energy diagnostic distortion (AWEDD) and multichannel PRD (MPRD) measures over different processing schemes such as multiscale principal component analysis (MSPCA) and multichannel empirical mode decomposition (MEMD)-based MECG compression and filtering. The normal and pathological MECG signals from the Physikalisch Technische Bundesanstalt (PTB) database is used in this work. The result shows that the proposed diagnostic distortion measure is effective to quantify the loss of clinical information in MECG signals.