Estimating the Severity of Obstructive Sleep Apnea Using ECG, Respiratory Effort and Neural Networks.

Journal: IEEE journal of biomedical and health informatics
Published Date:

Abstract

OBJECTIVE: wearable sensor technology has progressed significantly in the last decade, but its clinical usability for the assessment of obstructive sleep apnea (OSA) is limited by the lack of large and representative datasets simultaneously acquired with polysomnography (PSG). The objective of this study was to explore the use of cardiorespiratory signals common in standard PSGs which can be easily measured with wearable sensors, to estimate the severity of OSA.

Authors

  • Pedro Fonseca
    Philips Research, High Tech Campus 34, 5656 AE Eindhoven, The Netherlands. Department of Electrical Engineering, Eindhoven University of Technology, Postbus 513, 5600MB Eindhoven, The Netherlands.
  • Marco Ross
  • Andreas Cerny
    Epatocentro Ticino, Via Soldino 5, CH-6900, Lugano, Switzerland.
  • Peter Anderer
  • Fons Schipper
  • Angela Grassi
  • Merel van Gilst
  • Sebastiaan Overeem
    Sleep Medicine Center Kempenhaeghe, Heeze, The Netherlands.