Temporal Logic Based Monitoring of Assisted Ventilation in Intensive Care Patients

  • Sara Bufo
  • Ezio Bartocci
  • Guido Sanguinetti
  • Massimo Borelli
  • Umberto Lucangelo
  • Luca Bortolussi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8803)


We introduce a novel approach to automatically detect ineffective breathing efforts in patients in intensive care subject to assisted ventilation. The method is based on synthesising from data temporal logic formulae which are able to discriminate between normal and ineffective breaths. The learning procedure consists in first constructing statistical models of normal and abnormal breath signals, and then in looking for an optimally discriminating formula. The space of formula structures, and the space of parameters of each formula, are searched with an evolutionary algorithm and with a Bayesian optimisation scheme, respectively. We present here our preliminary results and we discuss our future research directions.


Temporal Logic Assist Ventilation Inspiratory Effort Statistical Model Check Bayesian Optimisation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Sara Bufo
    • 1
  • Ezio Bartocci
    • 2
  • Guido Sanguinetti
    • 3
    • 4
  • Massimo Borelli
    • 1
  • Umberto Lucangelo
    • 5
  • Luca Bortolussi
    • 1
    • 6
    • 7
  1. 1.Department of Mathematics and GeosciencesUniversity of TriesteItaly
  2. 2.Faculty of InformaticsVienna University of TechnologyAustria
  3. 3.School of InformaticsUniversity of EdinburghUK
  4. 4.SynthSys, Centre for Synthetic and Systems BiologyUniversity of EdinburghUK
  5. 5.Department of MedicineUniversity of TriesteItaly
  6. 6.Computer Science DepartmentSaarland UniversitySaarbrückenGermany
  7. 7.CNR/ISTIPisaItaly

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