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Pulse photoplethysmography derived respiration for obstructive sleep apnea detection

Abstract:

Five time series which are known to be modulated by respiration are derived from the pulse photoplethysmographic (PPG) signal, and they are analyzed for obstructive sleep apnea (OSA) detection: Pulse rate, amplitude, and width variabilities (PRV, PAV, and PWV, respectively), pulse upslopes, and slope transit time (STT). A total of 26 polysomnographic recordings were split in 1-min segments which were manually labeled as OSA (653 segments), normal breathing (7204 segments), or other pulmonary events. For each one of the 5 PPG-derived series, 4 features were extracted: the standard deviation, the power at high and low frequency (PLF) bands, and the normalized PLF. These 20 features were used as input of a least-squares support vector machine classifier using an RBF kernel. Results show an accuracy of 72.66%, suggesting that the analyzed features are promising for the detection of OSA from only the PPG signal.

Año de publicación:

2017

Keywords:

    Fuente:

    scopusscopus

    Tipo de documento:

    Conference Object

    Estado:

    Acceso abierto

    Áreas de conocimiento:

      Áreas temáticas:

      • Enfermedades
      • Fisiología humana

      Contribuidores:

      Raquel BailónRaquel Bailón
      Lazaro J.Lazaro J.
      Gil E.Gil E.
      Buyse B.Buyse B.
      Testelmans D.Testelmans D.
      Van Huffel S.Van Huffel S.
      Varon C.Varon C.
      Deviaene M.Deviaene M.