Title: Nonlinear methods of analysis to examine respiratory waveform variability during oral feeding in preterm infants

Authors: Caryn Bradley; Phyllis Guarrera-Bowlby; Harish Damodaran; Michael Ballintyn; James I. Hagadorn

Addresses: Department of Physical Therapy, University of California Irvine Medical Center, Newborn Intensive Care Unit, 101 The City Drive South, Orange, CA 92868, USA ' School of Health Related Professions, Rutgers University of New Jersey, Newark, NJ, USA ' River Rehabilitation and Movement Science Lab, Rutgers University of New Jersey, Newark, NJ, USA ' Biomedical Engineering Department, Hartford Hospital, Hartford, CT, USA ' School of Medicine, University of Connecticut, Division of Neonatology, Farmington, CT, USA; Connecticut Children's Medical Center, Hartford, CT, USA

Abstract: In a novel exploratory study, nonlinear methods of analysis for respiratory patterns were used to examine respiratory waveform variability during oral feeding in preterm infants. Twelve healthy preterm infants were studied using a within-subject cross over design to compare semi-upright and the elevated sidelying position during bottle feeding. Outcome measures were physiologic indicators of cardiopulmonary status: heart rate, respiratory rate, oxygen saturation and respiratory pattern variability. Preliminary results suggest that analysis of respiratory waveform variability is feasible and may be a more sensitive measure of cardiopulmonary physiology than means for heart rate, respiratory rate and percent haemoglobin oxygen saturation. Nonlinear methods of analysis of the respiratory data provide a distinct perspective on the adaptability of infants' breathing patterns while feeding. The clinical application of monitoring respiratory waveforms using nonlinear methods may be helpful in identifying readiness to initiate and advance feeds orally in preterm infants.

Keywords: nonlinear methods of analysis; respiratory waveform variability; oral feeding; preterm infants.

DOI: 10.1504/IJMEI.2017.085054

International Journal of Medical Engineering and Informatics, 2017 Vol.9 No.3, pp.284 - 298

Available online: 10 Apr 2017 *

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