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Lomb algorithm versus fast fourier transform in heart rate variability analyses of pain in premature infants

机译:LOMP算法与早产儿疼痛疼痛的快速傅里叶变换

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Heart rate variability analysis is a promising method for measuring pain in premature infants. The Lomb algorithm was adapted and compared with fast Fourier transform (FFT) for the purposes of PSD estimation. Both FFT and the Lomb algorithm had similar low frequency (LF) estimation error rates. However, the Lomb algorithm had a significant smaller error rate than FFT when estimating high frequency (HF). In addition, the ECG signals of two premature infants in the newborn intensive care unit were analyzed while undergoing a routine heel stick, a common painful procedure. The Lomb algorithm performed as expected marking a decrease in both LF and HF power in the presence of pain.
机译:心率变异性分析是一种衡量早产儿疼痛的有希望的方法。为PSD估计的目的,与快速傅里叶变换(FFT)进行了调整,并将LOMB算法进行了调整。 FFT和LOMB算法均具有相似的低频(LF)估计误差速率。然而,在估计高频(HF)时,LOMP算法比FFT具有显着的误差率。此外,在进行常规脚跟杆的同时分析了新生儿重症监护病房中的两个早产儿的ECG信号,是一种常见的痛苦程序。在存在疼痛的情况下,LOM算法随着预期的标记,标记LF和HF功率的降低。

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