Innovation in Bioengineering Research Group, University of Castilla-La Mancha, Campus Universitario, Cuenca, Spain.
Physiol Meas. 2012 Jun;33(6):969-84. doi: 10.1088/0967-3334/33/6/969. Epub 2012 May 4.
This paper proposes the first non-invasive method for direct and short-time regularity quantification of atrial fibrillatory (f) waves from the surface ECG in atrial fibrillation (AF). Regularity is estimated by computing individual morphological variations among f waves, which are delineated and extracted from the atrial activity (AA) signal, making use of an adaptive signed correlation index. The algorithm was tested on real AF surface recordings in order to discriminate atrial signals with different organization degrees, providing a notably higher global accuracy (90.3%) than the two non-invasive AF organization estimates defined to date: the dominant atrial frequency (70.5%) and sample entropy (76.1%). Furthermore, due to its ability to assess AA regularity wave to wave, the proposed method is also able to pursue AF organization time course more precisely than the aforementioned indices. As a consequence, this work opens a new perspective in the non-invasive analysis of AF, such as the individualized study of each f wave, that could improve the understanding of AF mechanisms and become useful for its clinical treatment.
本文提出了一种从房颤（AF）体表心电图中直接、短时间量化心房颤动（f）波规则性的无创方法。通过计算从心房活动（AA）信号中描绘和提取的 f 波之间的个体形态变化来估计规则性，利用自适应符号相关指数。该算法在真实的 AF 体表记录上进行了测试，以区分不同组织程度的心房信号，提供了明显更高的全局准确性（90.3%），高于迄今为止定义的两种非侵入性 AF 组织估计：主导心房频率（70.5%）和样本熵（76.1%）。此外，由于其能够逐波评估 AA 规则性，因此该方法也能够比上述指数更精确地追踪 AF 组织的时间过程。因此，这项工作为 AF 的非侵入性分析开辟了新的视角，例如对每个 f 波的个体化研究，这可以加深对 AF 机制的理解，并对其临床治疗有用。
