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Temporal Issues in the Intelligent Interpretation of the Sleep Apnea Syndrome

  • M. Cabrero-Canosa
  • M. Castro-Pereiro
  • M. Graña-Ramos
  • E. Hernandez-Pereira
  • V. Moret-Bonillo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2101)

Abstract

Automation of the medical diagnosis of the Sleep Apnea Syndrome (SAS) requires an intelligent analysis of the pneumological and neurophysiological signals of the patient that combines both conventional and Artificial Intelligence techniques in order to detect respiratory abnormalities and construct a hypnogram for the patient, and a process of temporal fusion and correlation between the signals for both a correct classification of the apneic events within a sleep stage framework, and to explain the occurrence of abnormal sleep patterns as a consequence of these events. In this article, the most im- portant aspects of the analysis and information integration processes are described and the preliminary validation results obtained are discussed.

Keywords

Positive Predictive Value Negative Predictive Value Sleep Stage Symbolic Information Intelligent Analysis 
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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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • M. Cabrero-Canosa
    • 1
  • M. Castro-Pereiro
    • 1
  • M. Graña-Ramos
    • 1
  • E. Hernandez-Pereira
    • 1
  • V. Moret-Bonillo
    • 1
  1. 1.Laboratory for Research and Development in Artificial Intelligence (LIDIA), Computer Science Dept.University of A CoruñaCoruñaSpain

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