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Estimation of breathing rate in thermal imaging videos: a pilot study on healthy human subjects

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Abstract

Diverse studies have demonstrated the importance of monitoring breathing rate (BR). Commonly, changes in BR are one of the earliest and major markers of serious complications/illness. However, it is frequently neglected due to limitations of clinically established measurement techniques, which require attachment of sensors. The employment of adhesive pads or thoracic belts in preterm infants as well as in traumatized or burned patients is an additional paramount issue. The present paper proposes a new robust approach, based on data fusion, to remotely monitor BR using infrared thermography (IRT). The algorithm considers not only temperature modulation around mouth and nostrils but also the movements of both shoulders. The data of these four sensors/regions of interest need to be further fused to reach improved accuracy. To investigate the performance of our approach, two different experiments (phase A: normal breathing, phase B: simulation of breathing disorders) on twelve healthy volunteers were performed. Thoracic effort (piezoplethysmography) was simultaneously acquired to validate our results. Excellent agreements between BR estimated with IRT and gold standard were achieved. While in phase A a mean correlation of 0.98 and a root-mean-square error (RMSE) of 0.28 bpm was reached, in phase B the mean correlation and the RMSE hovered around 0.95 and 3.45 bpm, respectively. The higher RMSE in phase B results predominantly from delays between IRT and gold standard in BR transitions: eupnea/apnea, apnea/tachypnea etc. Moreover, this study also demonstrates the capability of IRT to capture varied breathing disorders, and consecutively, to assess respiratory function. In summary, IRT might be a promising monitoring alternative to the conventional contact-based techniques regarding its performance and remarkable capabilities.

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References

  1. Abbas AK, Heimann K, Jergus K, Orlikowsky T, Leonhardt S. Neonatal non-contact respiratory monitoring based on real-time infrared thermography. Biomed Eng Online. 2011;10:93.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Al-Khalidi FQ, Saatchi R, Burke D, Elphick H, Tan S. Respiration rate monitoring methods: a review. Pediatr Pulmonol. 2011;46(6):523–9.

    Article  CAS  PubMed  Google Scholar 

  3. Atkins JH, Mandel JE. Performance of Masimo rainbow acoustic monitoring for tracking changing respiratory rates under laryngeal mask airway general anesthesia for surgical procedures in the operating room: a prospective observational study. Anesth Analg. 2014;119(6):1307–14.

    Article  PubMed  Google Scholar 

  4. Bartula M, Tigges T, Muehlsteff J. Camera-based system for contactless monitoring of respiration. In: Proceedings of IEEE engineering in medicine and biology society (IEEE, 2013). 2013. pp 2672–5

  5. Braun SR. Respiratory rate and pattern. In: Walker HK, Hall WD, Hurst JW, editors. Clinical methods: the history, physical, and laboratory examinations. 3rd ed. Boston: Butterworths; 1990 (chap 43).

    Google Scholar 

  6. Buist M, Bernard S, Nguyen TV, Moore G, Anderson J. Association between clinically abnormal observations and subsequent in-hospital mortality: a prospective study. Resuscitation. 2004;62(2):137–41.

    Article  PubMed  Google Scholar 

  7. Chen F, Wu H, Hsu PL, Stronger B, Sheridan R, Ma H. SmartPad: a wireless, adhesive-electrode-free, autonomous ECG acquisition system. In: Proceedings of IEEE engineering in medicine and biology society (IEEE, 2008). 2008. pp 2345–8

  8. Cretikos M, Chen J, Hillman K, Bellomo R, Finfer S, Flabouris A, study investigators M. The objective medical emergency team activation criteria: a case-control study. Resuscitation. 2007;73(1):62–72.

    Article  PubMed  Google Scholar 

  9. Cretikos MA, Bellomo R, Hillman K, Chen J, Finfer S, Flabouris A. Respiratory rate: the neglected vital sign. Med J Aust. 2008;188(11):657–9.

    PubMed  Google Scholar 

  10. Czaplik M, Biener I, Dembinski R, Pelosi P, Soodt T, Schroeder W, Leonhardt S, Marx G, Rossaint R, Bickenbach J. Analysis of regional compliance in a porcine model of acute lung injury. Respir Physiol Neurobiol. 2012;184(1):16–26.

    Article  PubMed  Google Scholar 

  11. Droitcour AD, Seto TB, Park BK, Yamada S, Vergara A, El Hourani C, Shing T, Yuen A, Lubecke VM, Boric-Lubecke O. Non-contact respiratory rate measurement validation for hospitalized patients. In: Proceedings of IEEE engineering in medicine and biology society (IEEE, 2009). 2009. pp 4812–15

  12. Duning T, Deppe M, Brand E, Stypmann J, Becht C, Heidbreder A. Young P Brainstem involvement as a cause of central sleep apnea: pattern of microstructural cerebral damage in patients with cerebral microangiopathy. PLoS ONE. 2013;8(4):e60,304.

    Article  Google Scholar 

  13. Elliott M, Coventry A. Critical care: the eight vital signs of patient monitoring. Br J Nurs. 2012;21(10):621–5.

    Article  PubMed  Google Scholar 

  14. Fei J, Pavlidis I. Virtual thermistor. In: Proceedings of IEEE engineering in medicine and biology society (IEEE, 2007). 2007. pp 250–3

  15. Fei J, Pavlidis I. Thermistor at a distance: unobtrusive measurement of breathing. IEEE Trans Biomed Eng. 2010;57(4):988–98.

    Article  PubMed  Google Scholar 

  16. Feldman JL, Del Negro CA. Looking for inspiration: new perspectives on respiratory rhythm. Nat Rev Neurosci. 2006;7(3):232.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Guechi Y, Pichot A, Frasca D, Rayeh-Pelardy F, Lardeur JY, Mimoz O. Assessment of noninvasive acoustic respiration rate monitoring in patients admitted to an Emergency Department for drug or alcoholic poisoning. J Clin Monit Comput. 2015;29(6):721–6.

    Article  PubMed  Google Scholar 

  18. Hall JE, Guyton AC. Guyton and hall textbook of medical physiology. 12th ed. Philadeiphia: Saunders; 2010.

    Google Scholar 

  19. Hess DR, MacIntyre NR, Galvin WF, Mishoe SC. Respiratory care: principles and practice. Burlington: Jones & Bartlett Publishers; 2015.

    Google Scholar 

  20. Huang Y, Young M, Huang K. Respiratory rate monitoring Gauze mask system based on a pyroelectric transducer. In: 2008 2nd international conference on bioinformatics and biomedical engineering, Shanghai. 2008. pp 1648–9.

  21. Jevon P. How to ensure patient observations lead to prompt identification of tachypnoea. Nurs Times. 2010;106(2):12–4.

    Google Scholar 

  22. Kowalak JP, editor. Lippincott’s Nursing Procedures. 5th ed. Baltimore: Lippincott Williams & Wilkins; 2009.

  23. Leonhardt S, Lachmann B. Electrical impedance tomography: the holy grail of ventilation and perfusion monitoring? Intensive Care Med. 2012;38(12):1917–29.

    Article  PubMed  Google Scholar 

  24. Lewis GF, Gatto RG, Porges SW. A novel method for extracting respiration rate and relative tidal volume from infrared thermography. Psychophysiology. 2011;48(7):877–87.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Liao P, Chen T, Chung P. A fast algorithm for multi-level thresholding. J Inform Sci Eng. 2001;17(5):713–27.

    Google Scholar 

  26. Lindh WQ, Pooler M, Tamparo CD, Dahl BM, Morris J. Delmar’s comprehensive medical assisting: administrative and clinical competencies. Boston: Cengage Learning; 2013.

    Google Scholar 

  27. McGain F, Cretikos MA, Jones D, Van Dyk S, Buist MD, Opdam H, Pellegrino V, Robertson MS, Bellomo R. Documentation of clinical review and vital signs after major surgery. Med J Aust. 2008;189(7):380–3.

    PubMed  Google Scholar 

  28. Mei X, Ling H. Robust visual tracking and vehicle classification via sparse representation. IEEE Trans Pattern Anal Mach Intell. 2011;33(11):2259–72.

    Article  PubMed  Google Scholar 

  29. Mimoz O, Benard T, Gaucher A, Frasca D, Debaene B. Accuracy of respiratory rate monitoring using a non-invasive acoustic method after general anaesthesia. Br J Anaesth. 2012;108(5):872–5.

    Article  CAS  PubMed  Google Scholar 

  30. Murthy R, Pavlidis I, Tsiamyrtzis P. Touchless monitoring of breathing function. In: Proceedings of IEEE engineering in medicine and biology society (IEEE, 2004). 2004. pp 1196–1199.

  31. O’Sullivan SB, Schmitz TJ, Fulk G. Physical rehabilitation. Duxbury: F.A. Davis; 2013.

    Google Scholar 

  32. Otsu N. A threshold selection method from gray-level histograms. IEEE Trans Syst Man Cybern. 1979;9(1):62–6.

    Article  Google Scholar 

  33. Pereira CB, Czaplik M, Blanik N, Rossaint R, Blazek V, Leonhardt S. Contact-free monitoring of circulation and perfusion dynamics based on the analysis of thermal imagery. Biomed Opt Expr. 2014;5(4):1075–89. doi:10.1364/BOE.5.001075.

    Article  Google Scholar 

  34. Pereira CB, Xinchi Yu, Blazek V, Leonhardt S. Robust remote monitoring of breathing function by using infrared thermography. In: Conference proceedings: ... annual international conference of the IEEE engineering in medicine and biology society. IEEE Engineering in Medicine and Biology Society. Annual Conference. 2015a. pp 4250–3

  35. Pereira CB, Yu X, Czaplik M, Rossaint R, Blazek V, Leonhardt S. Remote monitoring of breathing dynamics using infrared thermography. Biomed Opt Expr. 2015b;6(11):4378–94.

    Article  Google Scholar 

  36. Poh MZ, McDuff DJ, Picard RW. Non-contact, automated cardiac pulse measurements using video imaging and blind source separation. Opt Expr. 2010;18(10):10762–74.

    Article  CAS  Google Scholar 

  37. Riha RL. Diagnostic approaches to respiratory sleep disorders. J Thorac Dis. 2015;7(8):1373–84.

    PubMed  PubMed Central  Google Scholar 

  38. Rodríguez-Molinero A, Narvaiza L, Ruiz J, Gálvez-Barrón C. Normal respiratory rate and peripheral blood oxygen saturation in the elderly population. J Am Geriatr Soc. 2013;61(12):2238–40.

    Article  PubMed  Google Scholar 

  39. Shao D, Yang Y, Liu C, Tsow F, Yu H, Tao N. Noncontact monitoring breathing pattern, exhalation flow rate and pulse transit time. IEEE Trans Biomed Eng. 2014;61(11):2760–7.

    Article  PubMed  Google Scholar 

  40. Siccoli MM, Valko PO, Hermann DM, Bassetti CL. Central periodic breathing during sleep in 74 patients with acute ischemic stroke—neurogenic and cardiogenic factors. J Neurol. 2008;255(11):1687–92.

    Article  CAS  PubMed  Google Scholar 

  41. Soto RG, Fu ES, Vila H, Miguel RV. Capnography accurately detects apnea during monitored anesthesia care. Anesth Analg. 2004;99(2):379–82.

    Article  PubMed  Google Scholar 

  42. Strauß R, Ewig S, Richter K, König T, Heller G, Bauer TT. The prognostic significance of respiratory rate in patients with pneumonia: a retrospective analysis of data from 705,928 hospitalized patients in Germany from 2010–2012. Deutsches Ärzteblatt International. 2014;111(29–30):503–8.

    PubMed  PubMed Central  Google Scholar 

  43. Treas LS, Wilkinson JM. Basic nursing: concepts, skills, & reasoning. Duxbury: F.A. Davis; 2013.

    Google Scholar 

  44. Trobec R, Rashkovska A, Avbelj V. Two proximal skin electrodes–a respiration rate body sensor. Sensors. 2012;12(10):13813–28.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Wartzek T, Brüser C, Walter M, Leonhardt S. Robust sensor fusion of unobtrusively measured heart rate. IEEE J Biomed Health inform. 2014;18(2):654–60.

    Article  PubMed  Google Scholar 

  46. White G. Basic clinical lab competencies for respiratory care: an integrated approach. Boston: Cengage Learning; 2012.

    Google Scholar 

  47. Yoost B, Crawford L. Fundamentals of nursing: active learning for collaborative practice. 1st ed. Missouri: St. Louis; 2015.

    Google Scholar 

  48. Yuan G, Drost NA, McIvor R. Respiratory rate and breathing pattern. McMaster Univ Med J. 2013;10(1):23–8.

    Google Scholar 

  49. Zordan VB, Celly B, Chiu B, DiLorenzo PC. Breathe easy: model and control of human respiration for computer animation. Graph Models. 2006;68(2):113–32.

    Article  Google Scholar 

Download references

Acknowledgments

C. B. Pereira wishes to acknowledge FCT (Foundation for Science and Technology in Portugal) for her Ph.D. Grant SFRH/BD/84357/2012.

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Authors and Affiliations

  1. Chair for Medical Information Technology, Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany

    Carina Barbosa Pereira, Xinchi Yu, Vladimir Blazek, Boudewijn Venema & Steffen Leonhardt

  2. Department of Anesthesiology, University Hospital RWTH Aachen, Aachen, Germany

    Michael Czaplik

  3. Czech Institute of Informatics, Robotics and Cybernetics (CIIRC), CTU Prague, Prague, Czech Republic

    Vladimir Blazek

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  1. Carina Barbosa Pereira
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  2. Xinchi Yu
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Correspondence to Carina Barbosa Pereira.

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Barbosa Pereira, C., Yu, X., Czaplik, M. et al. Estimation of breathing rate in thermal imaging videos: a pilot study on healthy human subjects. J Clin Monit Comput 31, 1241–1254 (2017). https://doi.org/10.1007/s10877-016-9949-y

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