  A novel single-lead f-wave extraction algorithm based on the modern diffusion
geometry data analysis framework is proposed. The algorithm is essentially an
averaged beat subtraction algorithm, where the ventricular activity template is
estimated by combining a newly designed metric, the "diffusion distance," and
the non-local Euclidean median based on the non-linear manifold setup. We
coined the algorithm DD-NLEM. Two simulation schemes are considered, and the
new algorithm DD-NLEM outperforms traditional algorithms, including the average
beat subtraction, principal component analysis, and adaptive singular value
cancellation, in different evaluation metrics with statistical significance.
The clinical potential is shown in the real Holter signal, and we introduce a
new score to evaluate the performance of the algorithm.
