Browsing by Subject "AMPLITUDE"

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  • Ranta, Jukka; Airaksinen, Manu; Kirjavainen, Turkka; Vanhatalo, Sampsa; Stevenson, Nathan J. (2021)
    Objective To develop a non-invasive and clinically practical method for a long-term monitoring of infant sleep cycling in the intensive care unit. Methods Forty three infant polysomnography recordings were performed at 1-18 weeks of age, including a piezo element bed mattress sensor to record respiratory and gross-body movements. The hypnogram scored from polysomnography signals was used as the ground truth in training sleep classifiers based on 20,022 epochs of movement and/or electrocardiography signals. Three classifier designs were evaluated in the detection of deep sleep (N3 state): support vector machine (SVM), Long Short-Term Memory neural network, and convolutional neural network (CNN). Results Deep sleep was accurately identified from other states with all classifier variants. The SVM classifier based on a combination of movement and electrocardiography features had the highest performance (AUC 97.6%). A SVM classifier based on only movement features had comparable accuracy (AUC 95.0%). The feature-independent CNN resulted in roughly comparable accuracy (AUC 93.3%). Conclusion Automated non-invasive tracking of sleep state cycling is technically feasible using measurements from a piezo element situated under a bed mattress. Significance An open source infant deep sleep detector of this kind allows quantitative, continuous bedside assessment of infant's sleep cycling.
  • Stevenson, Nathan J.; Oberdorfer, Lisa; Tataranno, Maria-Luisa; Breakspear, Michael; Colditz, Paul B.; de Vries, Linda S.; Benders, Manon J. N. L.; Klebermass-Schrehof, Katrin; Vanhatalo, Sampsa; Roberts, James A. (2020)
    Objective A major challenge in the care of preterm infants is the early identification of compromised neurological development. While several measures are routinely used to track anatomical growth, there is a striking lack of reliable and objective tools for tracking maturation of early brain function; a cornerstone of lifelong neurological health. We present a cot-side method for measuring the functional maturity of the newborn brain based on routinely available neurological monitoring with electroencephalography (EEG). Methods We used a dataset of 177 EEG recordings from 65 preterm infants to train a multivariable prediction of functional brain age (FBA) from EEG. The FBA was validated on an independent set of 99 EEG recordings from 42 preterm infants. The difference between FBA and postmenstrual age (PMA) was evaluated as a predictor for neurodevelopmental outcome. Results The FBA correlated strongly with the PMA of an infant, with a median prediction error of less than 1 week. Moreover, individual babies follow well-defined individual trajectories. The accuracy of the FBA applied to the validation set was statistically equivalent to the training set accuracy. In a subgroup of infants with repeated EEG recordings, a persistently negative predicted age difference was associated with poor neurodevelopmental outcome. Interpretation The FBA enables the tracking of functional neurodevelopment in preterm infants. This establishes proof of principle for growth charts for brain function, a new tool to assist clinical management and identify infants who will benefit most from early intervention.
  • Nevalainen, Päivi; Marchi, Viviana; Metsäranta, Marjo; Lönnqvist, Tuula; Toiviainen-Salo, Sanna; Vanhatalo, Sampsa; Lauronen, Leena (2017)
    Objective: To evaluate the added value of somatosensory (SEPs) and visual evoked potentials (VEPs) recorded simultaneously with routine EEG in early outcome prediction of newborns with hypoxicischemic encephalopathy under modern intensive care. Methods: We simultaneously recorded multichannel EEG, median nerve SEPs, and flash VEPs during the first few postnatal days in 50 term newborns with hypoxic-ischemic encephalopathy. EEG background was scored into five grades and the worst two grades were considered to indicate poor cerebral recovery. Evoked potentials were classified as absent or present. Clinical outcome was determined from the medical records at a median age of 21 months. Unfavorable outcome included cerebral palsy, severe mental retardation, severe epilepsy, or death. Results: The accuracy of outcome prediction was 98% with SEPs compared to 90% with EEG. EEG alone always predicted unfavorable outcome when it was inactive (n = 9), and favorable outcome when it was normal or only mildly abnormal (n = 17). However, newborns with moderate or severe EEG background abnormality could have either favorable or unfavorable outcome, which was correctly predicted by SEP in all but one newborn (accuracy in this subgroup 96%). Absent VEPs were always associated with an inactive EEG, and an unfavorable outcome. However, presence of VEPs did not guarantee a favorable outcome. Conclusions: SEPs accurately predict clinical outcomes in newborns with hypoxic-ischemic encephalopathy and improve the EEG-based prediction particularly in those newborns with severely or moderately abnormal EEG findings. Significance: SEPs should be added to routine EEG recordings for early bedside assessment of newborns with hypoxic-ischemic encephalopathy. (C) 2017 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
  • Stevenson, N. J.; Oberdorfer, L.; Koolen, N.; O'Toole, J. M.; Werther, T.; Klebermass-Schrehof, K.; Vanhatalo, S. (2017)
    Minimally invasive, automated cot-side tools for monitoring early neurological development can be used to guide individual treatment and benchmark novel interventional studies. We develop an automated estimate of the EEG maturational age (EMA) for application to serial recordings in preterm infants. The EMA estimate was based on a combination of 23 computational features estimated from both the full EEG recording and a period of low EEG activity (46 features in total). The combination function (support vector regression) was trained using 101 serial EEG recordings from 39 preterm infants with a gestational age less than 28 weeks and normal neurodevelopmental outcome at 12 months of age. EEG recordings were performed from 24 to 38 weeks post-menstrual age (PMA). The correlation between the EMA and the clinically determined PMA at the time of EEG recording was 0.936 (95% CI: 0.932-0.976; n = 39). All infants had an increase in EMA between the first and last EEG recording and 57/62 (92%) of repeated measures within an infant had an increasing EMA with PMA of EEG recording. The EMA is a surrogate measure of age that can accurately determine brain maturation in preterm infants.
  • Antchev, G.; Aspell, P.; Atanassov, I.; Avati, V.; Baechler, J.; Berardi, V.; Berretti, M.; Bossini, E.; Bottigli, U.; Bozzo, M.; Broulim, P.; Burkhardt, H.; Buzzo, A.; Cafagna, F. S.; Campanella, C. E.; Catanesi, M. G.; Csanad, M.; Csorgo, T.; Deile, M.; De Leonardis, F.; D'Orazio, A.; Doubek, M.; Eggert, K.; Eremin, V.; Ferro, F.; Fiergolski, A.; Garcia, F.; Georgiev, V.; Giani, S.; Grzanka, L.; Guaragnella, C.; Hammerbauer, J.; Heino, J.; Karev, A.; Kaspar, J.; Kopal, J.; Kundrat, V.; Lami, S.; Latino, G.; Lauhakangas, R.; Linhart, R.; Lippmaa, E.; Lippmaa, J.; Lokajicek, M. V.; Naaranoja, T.; Oljemark, F.; Orava, R.; Österberg, K.; Saarikko, H.; Welti, J.; TOTEM Collaboration (2016)
    The TOTEM experiment at the CERN LHC has measured elastic proton-proton scattering at the centre-of-mass energy root s = 8 TeV and four-momentum transfers squared, vertical bar t vertical bar, from 6 x 10(-4) to 0.2GeV(2). Near the lower end of the t-interval the differential cross-section is sensitive to the interference between the hadronic and the electromagnetic scattering amplitudes. This article presents the elastic cross-section measurement and the constraints it imposes on the functional forms of the modulus and phase of the hadronic elastic amplitude. The data exclude the traditional Simplified West and Yennie interference formula that requires a constant phase and a purely exponential modulus of the hadronic amplitude. For parametrisations of the hadronic modulus with second-or third-order polynomials in the exponent, the data are compatible with hadronic phase functions giving either central or peripheral behaviour in the impact parameter picture of elastic scattering. In both cases, the.-parameter is found to be 0.12 +/- 0.03. The results for the total hadronic cross-section are sigma(tot) = (102.9 +/- 2.3) mb and (103.0 +/- 2.3) mb for central and peripheral phase formulations, respectively. Both are consistent with previous TOTEM measurements.