Skip to main content

Validity analysis of respiratory events of polysomnography using a plethysmography chest and abdominal belt

Sleep and Breathing volume 24, pages 127–134 (2020)Cite this article

Abstract

Purpose

Respiratory inductive plethysmography (RIP) is recommended as an alternative respiratory sensor for the identification of each apnea and hypopnea event in polysomnography. Using this sensor, the cumulative RIP results from the chest and abdomen (RIP sum) and time-derived results of the RIP sum (RIP flow) are calculated to track respiratory flow. However, the effectiveness of this sensor and the calculated respiratory results is still unclear, and validation studies for the scoring of respiratory events in polysomnography are rare.

Methods

Two hundred subjects were selected according to the severity of obstructive sleep apnea. A sleep specialist re-evaluated the respiratory events based on RIP flow data in a single-blind study. Statistical analysis was conducted with paired respiratory events scored in each of the RIP flow and polysomnography datasets.

Results

All respiratory events scored from the RIP flow were strongly correlated with those identified with standard sensors of polysomnography, regardless of disease severity. Most of the respiratory parameters from RIP flow trended toward underestimation. The RIP flow obtained from the alternative RIP sensor was appropriate for the diagnosis of obstructive sleep apnea based on a receiver operating characteristic curve.

Conclusions

Scored respiratory events from RIP flow data effectively reflected the respiratory flow and statistically correlated with the results from standard polysomnography sensors. Therefore, analyzing RIP flow utilizing an RIP sensor is considered a reliable method for respiratory event scoring.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

43,34 €

Price includes VAT (Finland)
Tax calculation will be finalised during checkout.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

References

  1. Bixler EO, Vgontzas AN, Ten Have T, Tyson K, Kales A (1998) Effects of age on sleep apnea in men: I. prevalence and severity. Am J Respir Crit Care Med 157(1):144–148

    CAS  Article  Google Scholar 

  2. Bixler EO, Vgontzas AN, Lin HM, Ten Have T, Rein J, Vela-Bueno A, Kales A (2001) Prevalence of sleep-disordered breathing in women: effects of gender. Am J Respir Crit Care Med 163(3 Pt 1):608–613

    CAS  Article  Google Scholar 

  3. Yaffe K, Laffan AM, Harrison SL, Redline S, Spira AP, Ensrud KE, Ancoli-Israel S, Stone KL (2011) Sleep-disordered breathing, hypoxia, and risk of mild cognitive impairment and dementia in older women. Jama 306(6):613–619

    CAS  Article  Google Scholar 

  4. Nieto FJ, Peppard PE, Young T, Finn L, Hla KM, Farre R (2012) Sleep-disordered breathing and cancer mortality: results from the Wisconsin leep Cohort Study. Am J Respir Crit Care Med 186(2):190–194

    Article  Google Scholar 

  5. Punjabi NM, Sorkin JD, Katzel LI, Goldberg AP, Schwartz AR, Smith PL (2002) Sleep-disordered breathing and insulin resistance in middle-aged and overweight men. Am J Respir Crit Care Med 165(5):677–682

    Article  Google Scholar 

  6. Yaggi HK, Concato J, Kernan WN, Lichtman JH, Brass LM, Mohsenin V (2005) Obstructive sleep apnea as a risk factor for stroke and death. N Engl J Med 353(19):2034–2041

    CAS  Article  Google Scholar 

  7. Aronson D, Nakhleh M, Zeidan-Shwiri T, Mutlak M, Lavie P, Lavie L (2014) Clinical implications of sleep disordered breathing in acute myocardial infarction. PLoS One 9(2):e88878

    Article  Google Scholar 

  8. Marin JM, Carrizo SJ, Vicente E, Agusti AG (2005) Long-term cardiovascular outcomes in men with obstructive sleep apnoea-hypopnoea with or without treatment with continuous positive airway pressure: an observational study. Lancet 365(9464):1046–1053

    Article  Google Scholar 

  9. Gurubhagavatula I, Patil S, Meoli A, Olson R, Sullivan S, Berneking M, Watson NF (2015) Sleep apnea evaluation of commercial motor vehicle operators. J Clin Sleep Med 12(3):285–286

    Article  Google Scholar 

  10. Kales SN, Czeisler CA (2016) Obstructive sleep apnea and work accidents: time for action. Sleep 39(6):1171–1173

    Article  Google Scholar 

  11. Filomeno R, Ikeda A, Tanigawa T (2016) Developing policy regarding obstructive sleep apnea and driving among commercial drivers in the United States and Japan. Ind Health 54(5):469–475

    Article  Google Scholar 

  12. McNicholas WT, Rodenstein D (2015) Sleep apnoea and driving risk: the need for regulation. Eur Respir Rev 24(138):602–606

    Article  Google Scholar 

  13. Rodenstein D (2008) Driving in Europe: the need of a common policy for drivers with obstructive sleep apnoea syndrome. J Sleep Res 17(3):281–284

    Article  Google Scholar 

  14. Berry RB, Budhiraja R, Gottlieb DJ, Gozal D, Iber C, Kapur VK, Marcus CL, Mehra R, Parthasarathy S, Quan SF, Redline S, Strohl KP, Davidson Ward SL, Tangredi MM (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):597–619

    Article  Google Scholar 

  15. Collop NA, Anderson WM, Boehlecke B, Claman D, Goldberg R, Gottlieb DJ, Hudgel D, Sateia M, Schwab R (2007) Clinical guidelines for the use of unattended portable monitors in the diagnosis of obstructive sleep apnea in adult patients. Portable monitoring task force of the American Academy of Sleep Medicine. J Clin Sleep Med 3(7):737–747

    Article  Google Scholar 

  16. Park do Y, Kim HJ, Kim CH, Kim YS, Choi JH, Hong SY, Jung JJ, Lee KI, Lee HS (2015) Reliability and validity testing of automated scoring in obstructive sleep apnea diagnosis with the Embletta X100. Laryngoscope 125(2):493–497

    CAS  Article  Google Scholar 

  17. Chadha TS, Watson H, Birch S, Jenouri GA, Schneider AW, Cohn MA, Sackner MA (1982) Validation of respiratory inductive plethysmography using different calibration procedures. Am Rev Respir Dis 125(6):644–649

    CAS  PubMed  Google Scholar 

  18. Cantineau JP, Escourrou P, Sartene R, Gaultier C, Goldman M (1992) Accuracy of respiratory inductive plethysmography during wakefulness and sleep in patients with obstructive sleep apnea. Chest 102(4):1145–1151

    CAS  Article  Google Scholar 

  19. Carry PY, Baconnier P, Eberhard A, Cotte P, Benchetrit G (1997) Evaluation of respiratory inductive plethysmography: accuracy for analysis of respiratory waveforms. Chest 111(4):910–915

    CAS  Article  Google Scholar 

  20. Loube DI, Andrada T, Howard RS (1999) Accuracy of respiratory inductive plethysmography for the diagnosis of upper airway resistance syndrome. Chest 115(5):1333–1337

    CAS  Article  Google Scholar 

  21. Witt JD, Fisher JR, Guenette JA, Cheong KA, Wilson BJ, Sheel AW (2006) Measurement of exercise ventilation by a portable respiratory inductive plethysmograph. Respir Physiol Neurobiol 154(3):389–395

    Article  Google Scholar 

  22. Grossman P, Wilhelm FH, Brutsche M (2010) Accuracy of ventilatory measurement employing ambulatory inductive plethysmography during tasks of everyday life. Biol Psychol 84(1):121–128

    Article  Google Scholar 

  23. Griffiths AG, Patwari PP, Loghmanee DA, Balog MJ, Trosman I, Sheldon SH (2017) Validation of polyvinylidene fluoride impedance sensor for respiratory event classification during polysomnography in children. J Clin Sleep Med 13(2):259–265

    Article  Google Scholar 

  24. Beattie ZT, Hayes TL, Guilleminault C, Hagen CC (2013) Accurate scoring of the apnea-hypopnea index using a simple non-contact breathing sensor. J Sleep Res 22(3):356–362

    Article  Google Scholar 

  25. Zhang Z, Zheng J, Wu H, Wang W, Wang B, Liu H (2012) Development of a respiratory inductive plethysmography module supporting multiple sensors for wearable systems. Sensors (Basel) 12(10):13167–13184

    Article  Google Scholar 

Download references

Funding

This was not an industry-supported study. This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2017R1E1A1A01074543). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author information

Affiliations

  1. Department of Otolaryngology, Ajou University School of Medicine, 164, Worldcup-ro, Yeongtong-gu, Suwon, 16499, Republic of Korea

    Do-Yang Park, Top Kim, Jung Jun Lee, Jung Ho Ha & Hyun Jun Kim

  2. Department of Medicine, Yonsei University Graduate School, Seoul, Republic of Korea

    Do-Yang Park

Authors
  1. Do-Yang Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Top Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jung Jun Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jung Ho Ha
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hyun Jun Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hyun Jun Kim.

Ethics declarations

Conflict of interest

The authors declare that they have no conflicts of interest.

Ethical approval

All procedures performed in the 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.

Informed consent

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

Additional information

Publisher’s note

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

Electronic supplementary material

Figure S1

Scoring of respiratory events with standard sensor and RIP signal. (a) Apnea, (b) Hypopnea, (c) RERA. RIP - respiratory inductive plethysmography; RERA - respiratory-effort-related arousal. (PDF 737 kb)

Figure S2

Misreading respiratory events with RIP signal, comparing with standard sensor at same time. (a) Misreading ‘Apnea’ to ‘Hypopnea’ from RIP Signal, (b) Misreading ‘Hypopnea’ to ‘Apnea’ from RIP signal, (c) Misreading ‘RERA’ to ‘spontaneous arousal’ from RIP signal. RIP - respiratory inductive plethysmography; RERA - respiratory-effort-related arousal. (PPTX 719 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Park, DY., Kim, T., Lee, J.J. et al. Validity analysis of respiratory events of polysomnography using a plethysmography chest and abdominal belt. Sleep Breath 24, 127–134 (2020). https://doi.org/10.1007/s11325-019-01940-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11325-019-01940-1

Keywords

  • Respiratory sensor
  • Validation
  • Polysomnography
  • Apnea
  • Scoring