IEEE Journal of Translational Engineering in Health and Medicine (Jan 2018)

Sleep Apnea Syndrome Sensing at C-Band

  • Xiaodong Yang,
  • Dou Fan,
  • Aifeng Ren,
  • Nan Zhao,
  • Zhiya Zhang,
  • Fangming Hu,
  • Weigang Wang,
  • Masood Ur Rehman,
  • Jie Tian

DOI
https://doi.org/10.1109/JTEHM.2018.2879085
Journal volume & issue
Vol. 6
pp. 1 – 8

Abstract

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A non-intrusive sleep apnea detection system using a C-Band channel sensing technique is proposed to monitor sleep apnea syndrome in real time. The system utilizes perturbations of RF signals to differentiate between patient's breathing under normal and sleep apnea conditions. The peak distance calculation is used to obtain the respiratory rates. A comparison of the datasets generated by the proposed method and a wearable sensor is made using a concordance correlation coefficient to establish its accuracy. The results show that the proposed sensing technique exhibits high accuracy and robustness, with more than 80% concordance with the wearable breathing sensor. This method is, therefore, a good candidate for the real-time wireless detection of sleep apnea.

Keywords