Skip to main content

Advertisement

Log in

Validation of noncontact cardiorespiratory monitoring using impulse-radio ultra-wideband radar against nocturnal polysomnography

  • Sleep Breathing Physiology and Disorders • Original Article
  • Published:
Sleep and Breathing Aims and scope Submit manuscript

Abstract

Purpose

Polysomnography (PSG) is a standard diagnostic test for obstructive sleep apnea (OSA). However, PSG requires many skin-contacted sensors to monitor vital signs of patients, which may also hamper patients’ sleep. Because impulse-radio ultra-wideband (IR-UWB) radar can detect the movements of heart and lungs without contact, it may be utilized for vital sign monitoring during sleep. Therefore, we aimed to verify the accuracy and reliability of the breathing rate (BR) and the heart rate (HR) measured by IR-UWB radar.

Method

Data acquisition with PSG and IR-UWB radar was performed simultaneously in 6 healthy volunteers and in 15 patients with suspected OSA. Subjects were divided into 4 groups (normal, mild OSA, moderate OSA, and severe OSA) according to the apnea-hypopnea index (AHI). BRs and HRs obtained from the radar using a software algorithm were compared with the BRs (chest belt) and the HRs (electrocardiography) obtained from the PSG.

Results

In normal and in mild OSA, BRs (intraclass correlation coefficients R [ICCR] 0.959 [0.956–0.961] and 0.957 [0.955–0.960], respectively) and HRs ([ICCR] 0.927 [0.922–0.931] and 0.926 [0.922–0.931], respectively) measured in the radar showed excellent agreement with those measured in PSG. In moderate and severe OSA, BRs ([ICCR] 0.957 [0.956–0.959] and 0.873 [0.864–0.882], respectively) and HRs ([ICCR] 0.907 [0.904–0.910] and 0.799 [0.784–0.812], respectively) from the two methods also agreed well.

Conclusions

The IR-UWB radar could accurately measure BRs and HRs in sleeping patients with OSA. Therefore, IR-UWB radar may be utilized as a cardiopulmonary monitor during sleep.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Lüthje L, Andreas S (2008) Obstructive sleep apnea and coronary artery disease. Sleep Med Rev 12(1):19–31. https://doi.org/10.1016/j.smrv.2007.08.002

    Article  PubMed  Google Scholar 

  2. Shamsuzzaman AM, Gersh BJ, Somers VK (2003) Obstructive sleep apnea: implications for cardiac and vascular disease. JAMA 290(14):1906–1914. https://doi.org/10.1001/jama.290.14.1906

    Article  CAS  PubMed  Google Scholar 

  3. Berry RB, Wagner MH (2015) Fundamentals 9 - polysomnography I. In: Berry RB, Wagner MH (eds) Sleep medicine pearls, Third edn. W.B. Saunders, Philadelphia, pp 80–87. https://doi.org/10.1016/B978-1-4557-7051-9.00009-7

    Chapter  Google Scholar 

  4. Verhulst SL, Schrauwen N, De Backer WA, Desager KN (2006) First night effect for polysomnographic data in children and adolescents with suspected sleep disordered breathing. Arch Dis Child 91(3):233–237. https://doi.org/10.1136/adc.2005.085365

    Article  CAS  PubMed  Google Scholar 

  5. Wang F, Tanaka M, Chonan S (2003) Development of a PVDF piezopolymer sensor for unconstrained in-sleep cardiorespiratory monitoring. J Intell Mater Syst Struct 14(3):185–190. https://doi.org/10.1177/1045389X03014003006

    Article  Google Scholar 

  6. Fei J, Pavlidis I (2010) Thermistor at a distance: unobtrusive measurement of breathing. IEEE Trans Biomed Eng 57(4):988–998. https://doi.org/10.1109/TBME.2009.2032415

    Article  PubMed  Google Scholar 

  7. Barbosa Pereira C, Czaplik M, Blazek V, Leonhardt S, Teichmann D (2018) Monitoring of cardiorespiratory signals using thermal imaging: a pilot study on healthy human subjects. Sensors (Basel) 18(5). https://doi.org/10.3390/s18051541

  8. Allen J (2007) Photoplethysmography and its application in clinical physiological measurement. Physiol Meas 28(3):R1–R39. https://doi.org/10.1088/0967-3334/28/3/R01

    Article  PubMed  Google Scholar 

  9. Lampe L, Witrisal K (2010) Challenges and recent advances in IR-UWB system design. Proceedings of 2010 IEEE International Symposium on Circuits and Systems (ISCAS), pp 3288–3291. https://doi.org/10.1109/ISCAS.2010.5537900

  10. Lee Y, Park JY, Choi YW, Park HK, Cho SH, Cho SH, Lim YH (2018) A novel non-contact heart rate monitor using impulse-radio ultra-wideband (IR-UWB) radar technology. Sci Rep 8(1):13053. https://doi.org/10.1038/s41598-018-31411-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Omachi TA (2011) Measures of sleep in rheumatologic diseases: Epworth sleepiness scale (ESS), functional outcome of sleep questionnaire (FOSQ), insomnia severity index (ISI), and Pittsburgh sleep quality index (PSQI). Arthritis Care Res 63 Suppl 11(0 11):S287–S296. https://doi.org/10.1002/acr.20544

    Article  Google Scholar 

  12. 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):479–504. https://doi.org/10.5664/jcsm.6506

    Article  PubMed  PubMed Central  Google Scholar 

  13. Berry RB, Brooks R, Gamaldo C, Harding SM, Lloyd RM, Quan SF, Troester MT, Vaughn BV (2017) AASM scoring manual updates for 2017 (version 2.4). J Clin Sleep Med 13(5):665–666. https://doi.org/10.5664/jcsm.6576

    Article  PubMed  PubMed Central  Google Scholar 

  14. Gaikwad AN, Singh D, Nigam MJ (2011) Application of clutter reduction techniques for detection of metallic and low dielectric target behind the brick wall by stepped frequency continuous wave radar in ultra-wideband range. IET Radar, Sonar & Navigation 5(4):416–425. https://doi.org/10.1049/iet-rsn.2010.0059

    Article  Google Scholar 

  15. Khan F, Cho SH (2017) A detailed algorithm for vital sign monitoring of a stationary/non-stationary human through IR-UWB radar. Sensors (Basel, Switzerland) 17(2):290. https://doi.org/10.3390/s17020290

    Article  Google Scholar 

  16. Leem KS, Khan F, Cho HS (2017) Vital sign monitoring and mobile phone usage detection using IR-UWB radar for intended use in Car crash prevention. Sensors 17(6). https://doi.org/10.3390/s17061240

  17. Lee JM, Choi JW, Cho SH (2016) Movement analysis during sleep using an IR-UWB radar sensor. 2016 IEEE international conference on network infrastructure and digital content (IC-NIDC), pp 486–490. https://doi.org/10.1109/ICNIDC.2016.7974622

  18. Kim B-H, Han S-J, Kwon G-R, Pyun J-Y (2015) Signal processing for tracking of moving object in multi-impulse radar network system. Int J Distrib Sens Netw 11(10):1–12. https://doi.org/10.1155/2015/536841

    Article  Google Scholar 

  19. Huang Q, Qu L, Wu B, Fang G (2010) UWB through-wall imaging based on compressive sensing. IEEE Trans Geosci Remote Sens 48(3):1408–1415. https://doi.org/10.1109/TGRS.2009.2030321

    Article  Google Scholar 

  20. Ren L, Wang H, Naishadham K, Kilic O, Fathy AE (2016) Phase-based methods for heart rate detection using UWB impulse Doppler radar. IEEE Transactions on Microwave Theory and Techniques 64(10):3319–3331. https://doi.org/10.1109/TMTT.2016.2597824

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the Bio & Medical Technology Development Program of the National Research Foundation (NRF) and was funded by the Korean government (MIST) (No. 2017M3A9E2064626).

Funding

This work was funded by the Korean government (MIST) (No. 2017M3A9E2064626).

Author information

Authors and Affiliations

Authors

Contributions

SK conducted the experiments and the processing of the data; YL performed statistical analysis; YHL and SeokHC conceived the research idea; SeokHC, YGL and SK wrote the paper; SungHC, YHL and HKP provided critical feedback on the paper.

Corresponding authors

Correspondence to Sung Ho Cho or Seok Hyun Cho.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

ESM 1

(PDF 1.23 MB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kang, S., Lee, Y., Lim, YH. et al. Validation of noncontact cardiorespiratory monitoring using impulse-radio ultra-wideband radar against nocturnal polysomnography. Sleep Breath 24, 841–848 (2020). https://doi.org/10.1007/s11325-019-01908-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11325-019-01908-1

Keywords

Navigation