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

doi:10.1109/ACSSC.2011.6190183

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 proceeding › Conference contribution

20 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 language	English (US)
Title of host publication	Conference Record of the 45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011
Pages	1098-1102
Number of pages	5
DOIs	https://doi.org/10.1109/ACSSC.2011.6190183
State	Published - 2011
Externally published	Yes
Event	45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011 - Pacific Grove, CA, United States Duration: Nov 6 2011 → Nov 9 2011

Publication series

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

Other

Other	45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011
Country/Territory	United States
City	Pacific Grove, CA
Period	11/6/11 → 11/9/11

ASJC Scopus subject areas

Signal Processing
Computer Networks and Communications

Access to Document

10.1109/ACSSC.2011.6190183

Cite this

Williamson, J. R., Bliss, D. W., Browne, D. W., Indic, P., Bloch-Salisbury, E., & Paydarfar, D. (2011). Using physiological signals to predict apnea in preterm infants. In Conference Record of the 45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011 (pp. 1098-1102). Article 6190183 (Conference Record - Asilomar Conference on Signals, Systems and Computers). https://doi.org/10.1109/ACSSC.2011.6190183

Using physiological signals to predict apnea in preterm infants. / Williamson, J. R.; Bliss, D. W.; Browne, D. W. et al.
Conference Record of the 45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011. 2011. p. 1098-1102 6190183 (Conference Record - Asilomar Conference on Signals, Systems and Computers).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Williamson, JR, Bliss, DW, Browne, DW, Indic, P, Bloch-Salisbury, E & Paydarfar, D 2011, Using physiological signals to predict apnea in preterm infants. in Conference Record of the 45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011., 6190183, Conference Record - Asilomar Conference on Signals, Systems and Computers, pp. 1098-1102, 45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011, Pacific Grove, CA, United States, 11/6/11. https://doi.org/10.1109/ACSSC.2011.6190183

Williamson JR, Bliss DW, Browne DW, Indic P, Bloch-Salisbury E, Paydarfar D. Using physiological signals to predict apnea in preterm infants. In Conference Record of the 45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011. 2011. p. 1098-1102. 6190183. (Conference Record - Asilomar Conference on Signals, Systems and Computers). doi: 10.1109/ACSSC.2011.6190183

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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.",

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Using physiological signals to predict apnea in preterm infants

Abstract

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