Detection of obstructive sleep apnea in ECG recordings using time-frequency distributions and dynamic features

@article{QuicenoManrique2009DetectionOO,
  title={Detection of obstructive sleep apnea in ECG recordings using time-frequency distributions and dynamic features},
  author={A. F. Quiceno-Manrique and Jes{\'u}s B. Alonso-Hern{\'a}ndez and C. M. Travieso-Gonzalez and Miguel Angel Ferrer-Ballester and Germ{\'a}n Castellanos-Dom{\'i}nguez},
  journal={2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
  year={2009},
  pages={5559-5562}
}
Detection of obstructive sleep apnea can be performed through heart rate variability analysis, since fluctuations of oxygen saturation in blood cause variations in the heart rate. Such variations in heart rate can be assessed by means of time-frequency analysis implemented with time-frequency distributions belonging to Cohen’s class. In this work, dynamic features are extracted from time frequency distributions in order to detect obstructive sleep apnea from ECG signals recorded during sleep… CONTINUE READING