Key result
Symbolic transfer entropy efficiently distinguishes normal signals, PVCs, and APBs.
Symbolic transfer entropy is a computationally efficient method that requires less data and can successfully distinguish between normal cardiac signals, premature ventricular contractions, and atrial premature beats.
May support efficient arrhythmia signal classification; leaves open prospective clinical validation before adoption.
In this paper, we use symbolic transfer entropy to study the coupling strength between premature signals. Numerical experiments show that three types of signal couplings are in the same direction. Among them, normal signal coupling is the strongest, followed by that of premature ventricular contractions, and that of atrial premature beats is the weakest. The T test shows that the entropies of the three signals are distinct. Symbolic transfer entropy requires less data, can distinguish the three types of signals and has very good computational efficiency.
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Wang et al. (2012) studied Premature cardiac signals (PVCs, APCs). Symbolic transfer entropy was evaluated on Coupling strength between premature signals. Symbolic transfer entropy successfully distinguished normal signals, premature ventricular contractions, and atrial premature beats with good computational efficiency.
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