Xiaochuan Du

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BACKGROUND Automatic detection of atrial fibrillation (AF) in electrocardiograms (ECGs) is beneficial for AF diagnosis, therapy, and management. In this article, a novel method of AF detection is introduced. Most current methods only utilize the RR interval as a critical parameter to detect AF; thus, these methods commonly confuse AF with other arrhythmias.(More)
Toll-like receptors (TLRs) are important pattern-recognition receptors (PRRs) that trigger innate immune response and mediate acquired immunity. Evidence has shown that SARM1 (sterile-α and TIR motif containing protein 1) is one of five TIR domain-containing adaptor proteins involved in TLRs signaling transduction. In the present study, a full-length cDNA(More)
⎯A semi-blind source extraction algorithm for noisy mixtures based on a linear predictor is proposed. The novel algorithm is firstly validated using the benchmark data and then is applied to extract array radar signal suffering from jamming interference. The results showed that the novel algorithm can effectively extract the target signal in radar echo.(More)
This article is to propose an algorithm for improving T-wave ends location during atrial fibrillation (AF). The traditional algorithms do not take the irregular baseline fibrillation of AF into consideration, so their location accuracy is relatively low. Based on simple assumptions that AF is a random signal while T waves and QRS complexes are deterministic(More)
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