Decomposition of tensors of cardio-vascular signals using CANDECOMP / PARAFAC algorithms

F. N. Almirantearena
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引用次数: 1

Abstract

In the processing of biological signals of the electrocardiogram (ECG) and Arterial Diameter Variation (ADV) there are several methods for the extraction of cardiovascular event characteristics. In this case, the canonical polyadic decomposition of CANDECOMP/PARAFAC (CP) tensors is used in the processing of the mixed signals of ECG-ADV; the ECG-ADV signals are extracted from each patient simultaneously and the detection quality of the ECG complex is verified. To do this, the ECG complex and the systolic wave of the ADV wave are aligned with Gaussian noise, and then the tensors were constructed for both signals. Five algorithms of CP were applied and the quality of the factorization of each one of the algorithms was checked with four indices. Both signals were shown to be non-collinear, and the algorithms that have the minimum number of iterations at the convergence were determined.
使用CANDECOMP / PARAFAC算法分解心血管信号张量
在心电图(ECG)和动脉直径变化(ADV)的生物信号处理中,有几种提取心血管事件特征的方法。在这种情况下,使用CANDECOMP/PARAFAC (CP)张量的正则多进分解来处理ECG-ADV的混合信号;同时提取每个患者的ECG- adv信号,验证心电图复合体的检测质量。为此,将心电复合体和ADV波的收缩期波与高斯噪声对齐,然后对这两个信号分别构造张量。应用了5种CP算法,并用4个指标检验了每种算法的分解质量。证明了两个信号都是非共线的,并确定了收敛处迭代次数最少的算法。
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