Using physiological signals to predict apnea in preterm infants

J. R. Williamson, D. W. Bliss, D. W. Browne, P. Indic, E. Bloch-Salisbury, D. Paydarfar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Scopus citations

Abstract

Apnea of prematurity, a common developmental disorder in preterm infants, is implicated in long-term neurodevelopmental deficits. Preventative clinical interventions, such as mechanosensory stimulation, would benefit from predictive knowledge of when the patient is at high risk for apnea. In this study, the predictive utility of features derived from breathing rate and heart rate is explored. Specifically, the multiscale correlation structure of interbreath intervals and heartbeat intervals is used to train a patient-specific apnea prediction algorithm. The algorithm's prediction results are significantly better than chance for three of the six patients it is evaluated on. These preliminary studies suggest that features of cardiopulmonary signals can anticipate the occurrence of clinically significant apneas in preterm infants.

Original languageEnglish (US)
Title of host publicationConference Record of the 45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011
Pages1098-1102
Number of pages5
DOIs
StatePublished - Dec 1 2011
Externally publishedYes
Event45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011 - Pacific Grove, CA, United States
Duration: Nov 6 2011Nov 9 2011

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393

Other

Other45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011
CountryUnited States
CityPacific Grove, CA
Period11/6/1111/9/11

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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