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Detection of High-frequency Respiratory Movements During Sleep

Tero Aittokallio, Mats Gyllenberg, Jaakko Järvi, Olli Polo, Olli Nevalainen, Detection of High-frequency Respiratory Movements During Sleep. TUCS Technical Reports 261, Turku Centre for Computer Science, 1999.

Abstract:

Sleep-related breathing disorders are common in adults and they have a significant impact on health and safety. In previous sleep studies it has come evident that many important breathing disorders can be monitored with the static-charge-sensitive bed (SCSB). A whole night sleep study produces a signal with considerable length, and therefore an automated analysis system would be of great need. In this work we focus on detection of high-frequency respiratory movement (HFRM) patterns which are related to an increased respiratory efforts. The paper documents four methods to automatically detect these patterns. The first two are based on classical statistical tests applied to the SCSB signal, and the other two use spectral characteristics in order to adaptively segment the SCSB signal. Finally we adjust each method to detect patterns that coincide with the HFRMs determined by an expert, and evaluate the performance of the methods using independent test data.

<p>Contact Olli Nevalainen (olli.nevalainen@cs.utu.fi) for the complete report.

BibTeX entry:

@TECHREPORT{tAiGyJaPo99a,
  title = {Detection of High-frequency Respiratory Movements During Sleep},
  author = {Aittokallio, Tero and Gyllenberg, Mats and Järvi, Jaakko and Polo, Olli and Nevalainen, Olli},
  number = {261},
  series = {TUCS Technical Reports},
  publisher = {Turku Centre for Computer Science},
  year = {1999},
  keywords = {breathing disorders, outlier, segmentation},
  ISBN = {952-12-0421-4},
}

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