Early detection of cerebral hypoxemia is an important aim in neonatology. A relevant parameter to assess brain oxygenation may be the cerebral tissue oxygen saturation (StO(2)) measured by near-infrared spectroscopy (NIRS). So far the reproducibility of StO(2) measurements was too low for clinical application, probably due to inhomogeneities. The aim of this study was to test a novel sensor geometry which reduces the influence of inhomogeneities. Thirty clinically stable newborn infants, with a gestational age of median 33.9 (range 26.9 to 41.9) weeks, birth weight of 2220 (820 to 4230) g, postnatal age of 5 (1 to 71) days were studied. At least four StO(2) measurements of 1 min duration were carried out using NIRS on the lateral head. The sensor was repositioned between measurements. Reproducibility was calculated by a linear mixed effects model. The mean StO(2) was 79.99 ± 4.47% with a reproducibility of 2.76% and a between-infant variability of 4.20%. Thus, the error of measurement only accounts for 30.1% of the variability. The novel sensor geometry leads to considerably more precise measurements compared to previous studies with, e.g., 5% reproducibility for the NIRO 300. The novel StO (2) Abstract. Early detection of cerebral hypoxemia is an important aim in neonatology. A relevant parameter to assess brain oxygenation may be the cerebral tissue oxygen saturation (StO 2 ) measured by near-infrared spectroscopy (NIRS). So far the reproducibility of StO 2 measurements was too low for clinical application, probably due to inhomogeneities. The aim of this study was to test a novel sensor geometry which reduces the influence of inhomogeneities. Thirty clinically stable newborn infants, with a gestational age of median 33.9 (range 26.9 to 41.9) weeks, birth weight of 2220 (820 to 4230) g, postnatal age of 5 (1 to 71) days were studied. At least four StO 2 measurements of 1 min duration were carried out using NIRS on the lateral head. The sensor was repositioned between measurements. Reproducibility was calculated by a linear mixed effects model. The mean StO 2 was 79.99 ± 4.47% with a reproducibility of 2.76% and a between-infant variability of 4.20%. Thus, the error of measurement only accounts for 30.1% of the variability. The novel sensor geometry leads to considerably more precise measurements compared to previous studies with, e.g., ∼5% reproducibility for the NIRO 300.
In studies with near-infrared spectroscopy, the recorded signals contain information on the temporal interbeat intervals of the heart. If this cardiac information is needed exclusively and could directly be extracted, an additional electrocardiography device would be unnecessary. The aim was to estimate these intervals from signals measured with near-infrared spectroscopy with two novel approaches. In one approach, we model the heartbeat oscillations in these signals with a Fourier series where the coefficients and the fundamental frequency can continuously change over time. The time-dependent model parameters are estimated and used to calculate the interbeat intervals. The second approach uses empirical mode decomposition. The signal measured with near-infrared spectroscopy is empirically decomposed into a set of oscillatory components. The sum of a specific subset of them is an estimate of the pure heartbeat signal in which the diastolic peaks and consequential interbeat intervals are detected. We show in simultaneous electrocardiography and near-infrared spectroscopy measurements on 11 subjects (8 men and 3 woman with mean age 32.8 ± 8.1 yr), that the interbeat intervals (and the consequential pulse rate variability measures), estimated using the proposed approaches, are in high agreement with their correspondents from electrocardiography. Estimating and validating the interbeat intervals of the heart using near-infrared spectroscopy on the human forehead Abstract. In studies with near-infrared spectroscopy, the recorded signals contain information on the temporal interbeat intervals of the heart. If this cardiac information is needed exclusively and could directly be extracted, an additional electrocardiography device would be unnecessary. The aim was to estimate these intervals from signals measured with near-infrared spectroscopy with two novel approaches. In one approach, we model the heartbeat oscillations in these signals with a Fourier series where the coefficients and the fundamental frequency can continuously change over time. The time-dependent model parameters are estimated and used to calculate the interbeat intervals. The second approach uses empirical mode decomposition. The signal measured with nearinfrared spectroscopy is empirically decomposed into a set of oscillatory components. The sum of a specific subset of them is an estimate of the pure heartbeat signal in which the diastolic peaks and consequential interbeat intervals are detected. We show in simultaneous electrocardiography and near-infrared spectroscopy measurements on 11 subjects (8 men and 3 woman with mean age 32.8 ± 8.1 yr), that the interbeat intervals (and the consequential pulse rate variability measures), estimated using the proposed approaches, are in high agreement with their correspondents from electrocardiography. C 2011 Society of Photo-Optical Instrumentation Engineers (SPIE).
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