Towards automated solutions for predictive monitoring of neonates

Rohan Joshi

Research output: ThesisPhd Thesis 1 (Research TU/e / Graduation TU/e)

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Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Department of Industrial Design
Supervisors/Advisors
  • Feijs, Loe M.G., Promotor
  • van Huffel, Sabine J.A., Promotor
  • Andriessen, Peter, Copromotor
  • van Pul, Carola, Copromotor
Award date30 Aug 2019
Place of PublicationEindhoven
Publisher
Print ISBNs978-94-6323-707-9
Publication statusPublished - 30 Aug 2019

Bibliographical note

Proefschrift

Keywords

  • patient monitoring
  • predictive monitoring
  • alarm fatigue
  • Kangaroo care
  • ballistography
  • Sepsis
  • respiration monitoring
  • heart rate variability
  • unobtrusive monitoring
  • wearable sensors
  • regression
  • Logistic regression
  • GLMM
  • Bayesian model
  • machine learning
  • Clinical Decision Support
  • NICU
  • preterm infants
  • neonates
  • prematurity
  • decision trees
  • Autonomic regulation
  • heart rate decelerations
  • cardiorespiratory coupling
  • cardiorespiratory instability

Promotion : time and place

  • 16.00h, Atlas, room 0.710

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