  This paper presents a novel signal compression algorithm based on the
Blaschke unwinding adaptive Fourier decomposition (AFD). The Blaschke unwinding
AFD is a newly developed signal decomposition theory. It utilizes the
Nevanlinna factorization and the maximal selection principle in each
decomposition step, and achieves a faster convergence rate with higher
fidelity. The proposed compression algorithm is applied to the
electrocardiogram signal. To assess the performance of the proposed compression
algorithm, in addition to the generic assessment criteria, we consider the less
discussed criteria related to the clinical needs -- for the heart rate
variability analysis purpose, how accurate the R peak information is preserved
is evaluated. The experiments are conducted on the MIT-BIH arrhythmia benchmark
database. The results show that the proposed algorithm performs better than
other state-of-the-art approaches. Meanwhile, it also well preserves the R peak
information.
