<p>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.</p><p>\&nbsp;</p>

Temporal Logic Based Monitoring of Assisted Ventilation in Intensive Care Patients

BORELLI, MASSIMO;LUCANGELO, UMBERTO;BORTOLUSSI, LUCA
2014-01-01

Abstract

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.

2014
http://dx.doi.org/10.1007/978-3-662-45231-8
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2827133
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