  Preterm infants with very low birth weight suffer from a high risk of
intra-ventricular hemorrhage(IVH) and other serious diseases. To improve the
clinical risk assessment of preterm infants and develop potential clinically
makers for the adverse outcome, the first part of the paper develops the
frequency spectral analysis on the non-invasively measured heart rate
variability, blood pressure variability and cerebral near-infrared spectroscopy
measures. Moderate and high correlations with the clinical risk index for
babies were identified from various spectral measures of arterial baroreflex
and cerebral autoregulation functions. It was also observed that the
cross-spectral transfer function analysis of cerebral NIRS and arterial blood
pressure was able to provide a number of parameters that were potentially
useful for distinguishing between preterm infants with or without IVH.
Furthermore, the detrended fluctuation analysis that quantifies the fractal
correlation properties of physiological signals has been examined, to determine
whether it could derive markers for the identification of preterm infants with
IVH. Cardiac output(CO) and total peripheral resistance(TPR) are two important
parameters of the cardiovascular system. Measurement of these two parameters
can provide valuable information for the assessment and management of patients
needing intensive care, including preterm infants in the neonatal intensive
care unit. To further assess the changes in CO and TPR in the preterm infants,
the multivariate regression model based on the useful features from ABP method
was used to improve the accuracy and robustness of the estimation. The
combination of signal analysis and multivariate regression model in estimation
of CO has produced some outcomes, and in the future, more effort should be
involved in this kind of research to improve the prediction of serious diseases
in preterm infants.
