Bayesian Online Changepoint Detection of Physiological Transitions

Alan H. Gee, Joshua Chang, Joydeep Ghosh, David Paydarfar

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

Abstract

Transition dynamics between two states can help elucidate the behavior of sequential events in physiological signals. By detecting transitions between healthy and pathological states within individual patients, we can help clinicians focus attention on critical transitions, to either preemptively treat adverse events or to detect changes resulting from treatments. We introduce a novel application of singlepoint Bayesian online changepoint detection to predict clinical state transitions, and apply this framework to detecting pathological transitions in preterm infants with episodes of apnea and bradycardia. Bayesian analysis of sequential physiological events provides insights on how to objectively classify clinically important state transitions that can be triggered by external or intrinsic mechanisms.

Original languageEnglish (US)
Title of host publication40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages45-48
Number of pages4
ISBN (Electronic)9781538636466
DOIs
StatePublished - Oct 26 2018
Event40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 - Honolulu, United States
Duration: Jul 18 2018Jul 21 2018

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2018-July
ISSN (Print)1557-170X

Conference

Conference40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
CountryUnited States
CityHonolulu
Period7/18/187/21/18

Fingerprint

Bayes Theorem
Apnea
Bradycardia
Premature Infants
Therapeutics

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Cite this

Gee, A. H., Chang, J., Ghosh, J., & Paydarfar, D. (2018). Bayesian Online Changepoint Detection of Physiological Transitions. In 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 (pp. 45-48). [8512204] (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2018-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2018.8512204

Bayesian Online Changepoint Detection of Physiological Transitions. / Gee, Alan H.; Chang, Joshua; Ghosh, Joydeep; Paydarfar, David.

40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 45-48 8512204 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2018-July).

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

Gee, AH, Chang, J, Ghosh, J & Paydarfar, D 2018, Bayesian Online Changepoint Detection of Physiological Transitions. in 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018., 8512204, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, vol. 2018-July, Institute of Electrical and Electronics Engineers Inc., pp. 45-48, 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018, Honolulu, United States, 7/18/18. https://doi.org/10.1109/EMBC.2018.8512204
Gee AH, Chang J, Ghosh J, Paydarfar D. Bayesian Online Changepoint Detection of Physiological Transitions. In 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 45-48. 8512204. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). https://doi.org/10.1109/EMBC.2018.8512204
Gee, Alan H. ; Chang, Joshua ; Ghosh, Joydeep ; Paydarfar, David. / Bayesian Online Changepoint Detection of Physiological Transitions. 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 45-48 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).
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