ID 原文 译文
40406 其次利用改进后的网络进行特征提取， Secondly, the modified network is used to extract the features.
40407 最后使用Softmax分类器进行分类。 Finally, the Softmax classifier is used for classification.
40408 在MIT-BIH心律不齐数据库中，提出的模型在没有任何额外人工特征和数据增强进行辅助的情况下，获得了97.20%的准确度、92.85%的敏感度、98.29%的特异性、93.16%的精确度和93.00%的F1分数。 In the MITBIH arrhythmia database, the proposed model achieves 97.20% accuracy, 92.85% sensitivity, 98.29%specificity, 93.16% accuracy and 93.00% F1 score without any additional artificial features and data augmentation.
40409 该研究将为医疗机构对于心电信号检测识别提供技术支撑，从而减轻专业医师的工作负荷。 This research will provide technical support for the detection and recognition of ECG signals to reduce the workload of professional doctors in medical institutions.
40410 房颤(Atrial fibrillation，AF)的患病率会随年龄的增加而增加，复发率也极高， The prevalence of atrial fibrillation(AF)increases with the age, and the recurrence rate is very high.
40411 因此提出一种快速准确检测AF的算法十分必要。 It is necessary to propose an accurate and fast algorithm to distinguish AF.
40412 本文基于第四统计力学原理，结合心脏系统的混沌性质与阴阳特性，提出区分AF和正常窦性心律(Normal sinus rhythm，NSR)的量化方法。 Based on the fourth statistical theory, a quantitative method for distinguishing AF from normal sinus rhythm(NSR) is proposed in this paper combining the chaos character and Yin Yang nature of heart system.
40413 首先以R-R间期数据构建嵌入维度为6、延时从1至30的相空间，依次得到对应的概率密度函数(Probability density function，PDF)图； Firstly, the phase space with embedding dimension of 6 and delay time from 1 to 30 is constructed by using R-R interval data.The probability density function(PDF)graph is obtained in turn.
40414 然后以PDF图的横轴作为强度ξ，纵轴概率的累加和作为分布函数x，利用ξ-x的对应关系拟合出第四统计力学参数k值； Then the horizontal axis of PDF graph is taken as strength ξ, the cumulative sum of longitudinal axis is taken as distribution function x, and the fourth statistical theory parameter k value is fitted by the corresponding relation of ξ-x.
40415 最后将得到的k值做微分累加得到Ksd值， Finally, differential summation with k and the result is defined as Ksd.