Electrocardiogram-based sleep analysis for sleep apnea screening and diagnosis

Sleep Breath. 2020 Mar;24(1):231-240. doi: 10.1007/s11325-019-01874-8. Epub 2019 Jun 21.


Purpose: Despite the increasing number of research studies of cardiopulmonary coupling (CPC) analysis, an electrocardiogram-based technique, the use of CPC in underserved population remains underexplored. This study aimed to first evaluate the reliability of CPC analysis for the detection of obstructive sleep apnea (OSA) by comparing with polysomnography (PSG)-derived sleep outcomes.

Methods: Two hundred five PSG data (149 males, age 46.8 ± 12.8 years) were used for the evaluation of CPC regarding the detection of OSA. Automated CPC analyses were based on ECG signals only. Respiratory event index (REI) derived from CPC and apnea-hypopnea index (AHI) derived from PSG were compared for agreement tests.

Results: CPC-REI positively correlated with PSG-AHI (r = 0.851, p < 0.001). After adjusting for age and gender, CPC-REI and PSG-AHI were still significantly correlated (r = 0.840, p < 0.001). The overall results of sensitivity and specificity of CPC-REI were good.

Conclusion: Compared with the gold standard PSG, CPC approach yielded acceptable results among OSA patients. ECG recording can be used for the screening or diagnosis of OSA in the general population.

Keywords: Autonomic nervous system; Cardiopulmonary coupling; Electrocardiogram; Obstructive sleep apnea; Polysomnography; Portable monitoring.

Publication types

  • Comparative Study

MeSH terms

  • Adult
  • Aged
  • Autonomic Nervous System / physiopathology
  • Electrocardiography / methods*
  • Female
  • Humans
  • Male
  • Mass Screening / methods*
  • Middle Aged
  • Outcome Assessment, Health Care
  • Polysomnography / methods*
  • Reproducibility of Results
  • Sleep Apnea, Obstructive / diagnosis*
  • Sleep Apnea, Obstructive / physiopathology