【摘要】：對(duì)健康的日常監(jiān)測(cè),時(shí)間長(zhǎng),數(shù)據(jù)量大.為了簡(jiǎn)化數(shù)據(jù)量,分析了現(xiàn)有的使用2~4個(gè)高斯函數(shù)擬合脈搏波的脈搏波數(shù)學(xué)建模方法,在此基礎(chǔ)上,提出了Lognormal函數(shù)模型的數(shù)學(xué)建模方法.使用4個(gè)Lognormal函數(shù)對(duì)脈搏波的一個(gè)周期進(jìn)行擬合建模,以脈搏波的生理特性為基礎(chǔ)調(diào)整4個(gè)Lognormal函數(shù)的起始時(shí)間點(diǎn),并對(duì)其性能進(jìn)行了分析對(duì)比.結(jié)果表明,與現(xiàn)有方法相比,Lognormal函數(shù)模型不僅有更高的擬合精確度,而且有更優(yōu)的計(jì)算復(fù)雜度,更適合以日常健康監(jiān)測(cè)為目的的體域網(wǎng)健康大數(shù)據(jù)應(yīng)用.
[Abstract]:Day-to-day monitoring of health, long time, large amount of data. In order to simplify the amount of data, the existing mathematical modeling method of pulse wave using 2-4 Gao Si functions to fit pulse wave is analyzed. On the basis of this, the mathematical modeling method of Lognormal function model is put forward. A period of pulse wave is modeled by using four Lognormal functions. Based on the physiological characteristics of pulse wave, the initial time points of four Lognormal functions are adjusted, and their performance is analyzed and compared. The results show that compared with the existing methods, the Lognormal function model not only has a higher fitting accuracy, but also has a better computational complexity. It is more suitable for the application of healthy big data in the body network for the purpose of daily health monitoring.
【作者單位】： 東北大學(xué)計(jì)算機(jī)科學(xué)與工程學(xué)院;
【基金】：國(guó)家科技支撐計(jì)劃項(xiàng)目(2012BAH82F04)
【分類號(hào)】：R443;O174

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