Validation of a portable monitoring device for the diagnosis of obstructive sleep apnea: electrocardiogram-based cardiopulmonary coupling

  • Mi Lu
  • Fang Fang
  • John E. Sanderson
  • Chenyao Ma
  • Qianqian Wang
  • Xiaojun Zhan
  • Fei Xie
  • Lei Xiao
  • Hu Liu
  • Hongyan Liu
  • Yongxiang WeiEmail author
Methods • Original Article



We aimed to evaluate the validity of the cardiopulmonary coupling (CPC) device, a limited-channel portable monitoring device for obstructive sleep apnea (OSA) screening in one single-center cohort, in particular in those with some cardiovascular diseases since the cardiopulmonary coupling might be different from those without.


Consecutive patients referred to the sleep medical center for assessment of possible OSA were enrolled in this study. Patients were examined with standard polysomnography (PSG) and CPC evaluation simultaneously. The results of the two examinations were compared in all subjects and in those with or without cardiovascular abnormalities.


A total of 179 subjects suspected with OSA were finally analyzed. According to OSA severity degree based on AHI, the area under ROC curve for the CPC device in the whole cohort patients was 0.79 (mild), 0.79 (moderate), and 0.86 (severe OSA), respectively (all p < 0.001). For patients with cardiovascular disease with different OSA severity, the area under the ROC curve was 0.86 (mild), 0.73 (moderate), and 0.83 (severe OSA), respectively (all p < 0.0001), and 0.74 (mild), 0.85 (moderate), and 0.91 (severe OSA), respectively in patients without cardiovascular disease (all p < 0.0001).


The overall performance of CPC technique was acceptable to assess OSA in subjects with clinical suspicion of OSA, and thus it might act as a fast tool to screen OSA patients. However, the sensitivity of CPC technology for patients with cardiovascular disease was relatively insufficient. Therefore, CPC technology should be carefully interpreted in OSA screening in those with cardiovascular disease.


Cardiopulmonary coupling analysis Validation Obstructive sleep apnea Cardiovascular disease 



American Academy of Sleep Medicine


apnea-hypopnea index


area under the ROC curve


body mass index


confidence interval


continuous positive airway pressure


cardiopulmonary coupling




ECG-derived respiration






elevated low-frequency coupling




Epworth Sleepiness Scale


high-frequency coupling


intraclass correlation


low-frequency coupling


lower limit


positive likelihood ratio


negative likelihood ratio


negative predictive value


obstructive sleep apnea


positive predictive value




receiver operating characteristics


standard deviation


sleep efficiency






total sleep time


upper limit


very-low-frequency coupling



The authors gratefully acknowledge the patients who have participated in this study and thank the staff at the sleep medical center, Beijing Anzhen Hospital, China, for scoring the PSG studies according to the updated AASM scoring guidelines. In addition, we also thank Nanjing Fengsheng Yongkang Software Technology Co., Ltd. for providing the CPC devices.

Authors’ contribution

Conception and design: Mi Lu, Fang Fang, and Yongxiang Wei. Collection and assembly of data: Mi Lu, Qianqian Wang, and Chenyao Ma. Data analysis and interpretation: Mi Lu and Fang Fang. PSG data scoring: Fei Xie, Lei Xiao, Hu Liu, Xiaojun Zhan, and Hongyan Liu. Manuscript writing: Mi Lu, Fang Fang, and John E. Sanderson. Revised the language/article: Mi Lu, Fang Fang, John E. Sanderson, and Xiaojun Zhan. Final approval of manuscript: all authors.


This study was supported by NSFC (Project 81870335), Beijing Medical Project 2016-4, the Beijing Key Laboratory of Upper Airway Dysfunction and Related Cardiovascular Diseases (BZ0377), Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support (ZYLX201605), Beijing Municipal Science and Technology Commission (Z141100006014057), and the project of Beijing Institute of Heart Lung and Blood Vessel Diseases (2018S14).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflicts of interest.

Ethical approval

This study was approved by the local institutional review board of Beijing Anzhen Hospital (Capital Medical University, Beijing, China). All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.


  1. 1.
    Young T, Palta M, Dempsey J, Skatrud J, Weber S, Badr S (1993) The occurrence of sleep-disordered breathing among middle-aged adults. N Engl J Med 328(17):1230–1235CrossRefGoogle Scholar
  2. 2.
    Sánchez-de-la-Torre M, Campos-Rodriguez F, Barbé F (2013) Obstructive sleep apnoea and cardiovascular disease. Lancet Respir Med 1(1):61–72CrossRefPubMedGoogle Scholar
  3. 3.
    Yumino D, Wang H, Floras JS, Newton GE, Mak S, Ruttanaumpawan P, Parker JD, Bradley TD (2009) Prevalence and physiological predictors of sleep apnea in patients with heart failure and systolic dysfunction. J Card Fail 15(4):279–285CrossRefPubMedGoogle Scholar
  4. 4.
    Lyons OD, Ryan CM (2015) Sleep apnea and stroke. Can J Cardiol 31(7):918–927CrossRefPubMedGoogle Scholar
  5. 5.
    Li M, Li X, Lu Y (2018) Obstructive sleep apnea syndrome and metabolic diseases. Endocrinology 159(7):2670–2675CrossRefPubMedGoogle Scholar
  6. 6.
    Tregear S, Reston J, Schoelles K, Phillips B (2009) Obstructive sleep apnea and risk of motor vehicle crash: systematic review and meta-analysis. J Clin Sleep Med 5(6):573–581PubMedPubMedCentralGoogle Scholar
  7. 7.
    Kendzerska T, Mollayeva T, Gershon AS, Leung RS, Hawker G, Tomlinson G (2014) Untreated obstructive sleep apnea and the risk for serious long-term adverse outcomes: a systematic review. Sleep Med Rev 18(1):49–59CrossRefPubMedGoogle Scholar
  8. 8.
    Kapur V, Blough DK, Sandblom RE, Hert R, de Maine JB, Sullivan SD, Psaty BM (1999) The medical cost of undiagnosed sleep apnea. Sleep 22(6):749–755CrossRefPubMedGoogle Scholar
  9. 9.
    Young T, Evans L, Finn L, Palta M (1997) Estimation of the clinically diagnosed proportion of sleep apnea syndrome in middle-aged men and women. Sleep 20(9):705–706CrossRefPubMedGoogle Scholar
  10. 10.
    Kapur VK, Auckley DH, Chowdhuri S, Kuhlmann DC, Mehra R, Ramar K, Harrod CG (2017) Clinical practice guideline for diagnostic testing for adult obstructive sleep apnea: an American Academy of Sleep Medicine Clinical Practice Guideline. J Clin Sleep Med 13(3):479–504CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Thomas RJ, Mietus JE, Peng CK, Gilmartin G, Daly RW, Goldberger AL, Gottlieb DJ (2007) Differentiating obstructive from central and complex sleep apnea using an automated electrocardiogram-based method. Sleep 30(12):1756–1769CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Atri R, Mohebbi M (2015) Obstructive sleep apnea detection using spectrum and bispectrum analysis of single-lead ECG signal. Physiol Meas 36(9):1963–1980CrossRefPubMedGoogle Scholar
  13. 13.
    Harrington J, Schramm PJ, Davies CR, Lee-Chiong TL (2013) An electrocardiogram-based analysis evaluating sleep quality in patients with obstructive sleep apnea. Sleep Breath 17(3):1071–1078CrossRefPubMedGoogle Scholar
  14. 14.
    Thomas RJ, Mietus JE, Peng CK, Goldberger AL (2005) An electrocardiogram-based technique to assess cardiopulmonary coupling during sleep. Sleep 28(9):1151–1161CrossRefPubMedGoogle Scholar
  15. 15.
    Magnusdottir S, Hilmisson H (2018) Ambulatory screening tool for sleep apnea: analyzing a single-lead electrocardiogram signal (ECG). Sleep Breath 22(2):421–429CrossRefPubMedGoogle Scholar
  16. 16.
    Huikuri HV, Stein PK. Heart rate variability in risk stratification of cardiac patients (2013) Prog Cardiovasc Dis 56(2): 153–159Google Scholar
  17. 17.
    Kushida CA, Littner MR, Morgenthaler T, Alessi CA, Bailey D, Coleman J, Friedman L (2005) Practice parameters for the indications for polysomnography and related procedures: an update for 2005. Sleep 28(4):499–521CrossRefPubMedGoogle Scholar
  18. 18.
    Berry RB, Budhiraja R, Gottlieb DJ, Gozal D, Iber C, Kapur VK, Marcus CL, Mehra R (2012) Rules for scoring respiratory events in sleep: update of the 2007 AASM Manual for the Scoring of Sleep and Associated Events. Deliberations of the Sleep Apnea Definitions Task Force of the American Academy of Sleep Medicine. J Clin Sleep Med 8(5):597–619PubMedPubMedCentralGoogle Scholar
  19. 19.
    Bibbins-Domingo K, Grossman DC, Curry SJ, Davidson KW (2017) Screening for obstructive sleep apnea in adults: US Preventive Services Task Force recommendation statement. JAMA 317(4):407–414CrossRefPubMedGoogle Scholar
  20. 20.
    Thomas RJ (2016) Cardiopulmonary coupling sleep spectrograms. In: Kryger MH, Roth T, Dement WC (eds) Principles and practice of sleep medicine, 6rd edn. Elsevier, Inc., Philadelphia, pp 1615–1623Google Scholar
  21. 21.
    Archontogeorgis K, Voulgaris A, Nena E, Strempela M, Karailidou P, Tzouvelekis A, Mouemin T (2018) Cardiovascular risk assessment in a cohort of newly diagnosed patients with obstructive sleep apnea syndrome. Cardiol Res Pract 2018:6572785CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Galinier M, Pathak A, Fourcade J, Androdias C, Curnier D, Varnous S, Boveda S, Massabuau P (2000) Depressed low frequency power of heart rate variability as an independent predictor of sudden death in chronic heart failure. Eur Heart J 21(6):475–482CrossRefPubMedGoogle Scholar
  23. 23.
    Huikuri HV, Stein PK (2012) Clinical application of heart rate variability after acute myocardial infarction. Front Physiol 3:41CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Knowlton AA, Lee AR (2012) Estrogen and the cardiovascular system. Pharmacol Ther 135(1):54–70CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Kendzerska T, Gershon AS, Atzema C, Dorian P, Mangat I, Hawker G, Leung RS (2018) Sleep apnea increases the risk of new hospitalized atrial fibrillation: a historical cohort study. Chest 154(6):1330–1339CrossRefPubMedGoogle Scholar
  26. 26.
    Chan J, Sanderson J, Chan W, Lai C, Choy D, Ho A, Leung R (1997) Prevalence of sleep-disordered breathing in diastolic heart failure. Chest 111(6):1488–1493CrossRefPubMedGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.The Key Laboratory of Upper Airway Dysfunction-Related Cardiovascular DiseasesBeijing Institute of Heart, Lung and Blood Vessel DiseasesBeijingChina
  2. 2.Department of Sleep Medical Center, Beijing Anzhen HospitalCapital Medical UniversityBeijingChina

Personalised recommendations