Research Group in Electronic, Biomedical and Telecommunication Engineering, University of Castilla-La Mancha, Albacete, Spain.
Physiol Meas. 2019 Jul 30;40(7):075003. doi: 10.1088/1361-6579/ab2cb8.
The most relevant source of signal contamination in the cardiac electrophysiology (EP) laboratory is the ubiquitous powerline interference (PLI). To reduce this perturbation, algorithms including common fixed-bandwidth and adaptive-notch filters have been proposed. Although such methods have proven to add artificial fractionation to intra-atrial electrograms (EGMs), they are still frequently used. However, such morphological alteration can conceal the accurate interpretation of EGMs, specially to evaluate the mechanisms supporting atrial fibrillation (AF), which is the most common cardiac arrhythmia. Given the clinical relevance of AF, a novel algorithm aimed at reducing PLI on highly contaminated bipolar EGMs and, simultaneously, preserving their morphology is proposed.
The method is based on the wavelet shrinkage and has been validated through customized indices on a set of synthesized EGMs to accurately quantify the achieved level of PLI reduction and signal morphology alteration. Visual validation of the algorithm's performance has also been included for some real EGM excerpts.
The method has outperformed common filtering-based and wavelet-based strategies in the analyzed scenario. Moreover, it possesses advantages such as insensitivity to amplitude and frequency variations in the PLI, and the capability of joint removal of several interferences.
The use of this algorithm in routine cardiac EP studies may enable improved and truthful evaluation of AF mechanisms.
心脏电生理学（EP）实验室中最相关的信号污染源是普遍存在的电源线干扰（PLI）。为了减少这种干扰，已经提出了包括常见固定带宽和自适应陷波滤波器在内的算法。尽管这些方法已被证明会对内腔电图（EGM）添加人为的分数化，但它们仍经常被使用。然而，这种形态改变可能会掩盖 EGM 的准确解释，特别是在评估支持心房颤动（AF）的机制时，AF 是最常见的心律失常。鉴于 AF 的临床相关性，提出了一种旨在减少高度污染的双极 EGM 上的 PLI 并同时保留其形态的新算法。
该方法基于小波收缩，并通过一组合成的 EGM 上的定制指标进行了验证，以准确量化所达到的 PLI 减少水平和信号形态改变程度。还包括一些真实 EGM 摘录的算法性能的可视化验证。
在分析的情况下，该方法优于常见的基于滤波和基于小波的策略。此外，它具有不受 PLI 幅度和频率变化影响的优点，并且能够联合去除多个干扰。
在常规心脏 EP 研究中使用该算法可以改善对 AF 机制的评估。
