Dealing with Imprecision in the Sleep Apnea-Hypopnea Syndrome

D. lvarez-Estvez and V. Moret-Bonillo (Spain)

Keywords

Sleep ApneaHipopnea Syndrome, Artificial Intelligence, Fuzzy Reasoning

Abstract

The sleep apnea/hypopnea syndrome is characterised by the repeated occurrence of involuntary pauses in breathing during a night’s sleep. Depending on the extent of these pauses, they are classified as apneas or hypopneas. In order to carry out their identification an analysis of respiratory signals recorded for an entire night’s sleep is necessary. Locating and classifying apneic events is a complex task, given the error associated with the process for digitising signals, variability in expert criteria and the complexity of the signals themselves. This article describes a fuzzy-logic-based automated system for detecting apneic events and classifying them as apneas or hypopneas. The aim is to equip this system with mechanisms for dealing with imprecision and reasoning affected by uncertainty.

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