基于数学工具的心率变异性生成

Proceedings of the 19th International Conference on Computer Systems and Technologies Pub Date : 2018-09-13 DOI:10.1145/3274005.3274035

G. Georgieva-Tsaneva

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引用次数: 3

摘要

本文提出了一种利用数学工具生成合成心率变异性(HRV)数据的算法。生成的数据包括低频Mayer波、高频频谱上呼吸窦性心律失常的影响以及极低频范围内体温调节、身体活动等因素的影响。该算法使用小波变换将生成的数据转换到时域。在时域和频域对生成的HRV序列进行了研究。结果表明，生成的HRV数据与健康个体相对应。该算法可用于评估由患者心电图数据得出的真实HRV序列的诊断能力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Heart Rate Variability Generating Based on Matematical Tools

The article presents an algorithm for generating sysnthetic Heart Rate Variability (HRV) data using mathematical tools. The generated data includes the low frequency Mayer wave, the effect of Respiratory Sinus Arrhythmia on the high frequency spectrum and the influence of thermoregulation, physical activity, etc. factors in the very low frequency range. The algorithm uses a wavelet transformation to convert the generated data into the time domain. The generated HRV series has been investigated in the time and frequency domains. The results show that the generated HRV data corresponds to a healthy individual. The algorithm can be used to evaluate the diagnostic capabilities of real HRV sequences derived from patient electrocardiographic data.

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Proceedings of the 19th International Conference on Computer Systems and Technologies

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