  The severity of atrial fibrillation (AF) can be assessed from intra-operative
epicardial measurements (high-resolution electrograms), using metrics such as
conduction block (CB) and continuous conduction delay and block (cCDCB). These
features capture differences in conduction velocity and wavefront propagation.
However, they do not clearly differentiate patients with various degrees of AF
while they are in sinus rhythm, and complementary features are needed. In this
work, we focus on the morphology of the action potentials, and derive features
to detect variations in the atrial potential waveforms. Methods: We show that
the spatial variation of atrial potential morphology during a single beat may
be described by changes in the singular values of the epicardial measurement
matrix. The method is non-parametric and requires little preprocessing. A
corresponding singular value map points at areas subject to fractionation and
block. Further, we developed an experiment where we simultaneously measure
electrograms (EGMs) and a multi-lead ECG. Results: The captured data showed
that the normalized singular values of the heartbeats during AF are higher than
during SR, and that this difference is more pronounced for the (non-invasive)
ECG data than for the EGM data, if the electrodes are positioned at favorable
locations. Conclusion: Overall, the singular value-based features are a useful
indicator to detect and evaluate AF. Significance: The proposed method might be
beneficial for identifying electropathological regions in the tissue without
estimating the local activation time.
