Study and Analysis of Electrocardiography Signals for Computation of R Peak Value for Sleep Apnea Patient

  • Mridu Sahu
  • Saransh Shirke
  • Garima Pathak
  • Prashant Agarwal
  • Ravina Gupta
  • Vishal Sodhi
  • N. K. Nagwani
  • Shrish Verma
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 381)


In this work, identification of sleep apnea symptoms is performed using Electrocardiography (ECG). ECG wave analysis is performed for sleep apnea patient. Sleep Apnea is a type of sleep disorder and it is also recognized by polysomnography (PSG) devices. Proposed article uses eight male patient data of similar age group (ranging from 51 to 53) and similar height (ranging from 173 to 179). The article found a relationship between the varying degrees of sleep apnea and the corresponding R peak value. First, ECG signal is preprocessed and then R peak value of different apnea patients is calculated.


Sleep apnea Electrocardiography (ECG) Polysomnography (PSG) R peak value 



This research is supported by the National Institute of Technology, Raipur and thanks to Physionet Repository as well as Dr. Thomas Penzel for the ECG corpus and to matlab group for the experimental execution.


  1. 1.
    Saritha, C., Sukanya, V., Narasimha, Y.: Murthy: ECG signal analysis using wavelet transforms. Bulg. J. Phys. 35(1), 68–77 (2008)MATHGoogle Scholar
  2. 2.
    McMurray, J.J.V., Adamopoulos, S., Anker, S.D., Auricchio, A., Böhm, M., Dickstein, K., Falk, V.:: ESC guidelines for the diagnosis and treatment of acute and chronic heart failure 2012. Eur. J. Heart Fail. 14(8), 803–869 (2012)Google Scholar
  3. 3.
    Sullivan, C.E., Lynch, C.: Device and method for monitoring breathing during sleep, control of CPAP treatment, and preventing of apnea. U.S. patent 5,245,995, 21 Sept 1993Google Scholar
  4. 4.
    Kohler, B.-U., Hennig, C., Orglmeister, R.: The principles of software QRS detection. IEEE Eng. Med. Biol. Mag. 21(1), 42–57 (2002)Google Scholar
  5. 5.
    Mirvis, D.M., Goldberger, A.L.: Electrocardiography. In: Heart Disease: A Textbook of Cardiovascular Medicine, 6th ed, p. 100-1. WB Saunders, Philadelphia (2001)Google Scholar
  6. 6.
    Im, K.B., Strader, S., Dyken, M.E.: Management of sleep disorders in stroke. Curr. Treat. Opt. Neurol. 12(5), 379–395 (2010)Google Scholar
  7. 7.
    Lund, H.G., Reider, B.D., Whiting, A.B., Roxanne Prichard, J.: Sleep patterns and predictors of disturbed sleep in a large population of college students. J. Adolesc. Health 46(2), 124–132 (2010)Google Scholar
  8. 8.
  9. 9.
    Johns, M.W.: A new method for measuring daytime sleepiness: the Epworth sleepiness scale. Sleep 14(6), 540–545 (1991)Google Scholar
  10. 10.
    He, J., Kryger, M.H., Zorick, F.J., Conway, W., Roth, T.: Mortality and apnea index in obstructive sleep apnea. Experience in 385 male patients. FREE TO VIEW. Chest 94(1), 9–14 (1988)CrossRefGoogle Scholar
  11. 11.
    Mezzanotte, W.S., Tangel, D.J., White, D.P.: Waking genioglossal electromyogram in sleep apnea patients versus normal controls (a neuromuscular compensatory mechanism). J. Clin. Invest. 89(5), 1571 (1992)Google Scholar
  12. 12.
    Kinio, S., Islam, M., Qasim, T.: Central sleep apnea detection and stimulation. In: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society, Conference, vol. 2011, pp. 7626–7629 (2010)Google Scholar
  13. 13.
  14. 14.
    Malhotra, A., White, D.P.: Obstructive sleep apnoea. Lancet 360(9328), 237–245 (2002)CrossRefGoogle Scholar
  15. 15.
    Carroll, J.L., McColley, S.A., Marcus, C.L., Curtis, S., Loughlin, G.M.: Inability of clinical history to distinguish primary snoring from obstructive sleep apnea syndrome in children. CHEST J. 108(3), 610–618 (1995)Google Scholar
  16. 16.
    Barnes, M., McEvoy, R.D., Banks, S., Tarquinio, N., Murray, C.G., Vowles, N., Pierce, R.J.: Efficacy of positive airway pressure and oral appliance in mild to moderate obstructive sleep apnea. Am. J. Respir. Crit. Care Med. 170(6), 656–664 (2004)Google Scholar
  17. 17.
    Strohl, K.P., Redline, S.: Recognition of obstructive sleep apnea. Am. J. Respir. Crit. Care Med. 154(2), 279–289 (1996)Google Scholar
  18. 18.
    Sahu, M., Nagwani, N.K., Verma, S., Shirke, S.: An incremental feature reordering (IFR) algorithm to classify eye state identification using EEG. In: Information Systems Design and Intelligent Applications, pp. 803–811. Springer India, (2015)Google Scholar
  19. 19.
    Protik, M., Rahman, N., Khatun, F., Islam, M.M.: Analyzing QRS complex, ST segment and QT interval of ECG signal to determine the effect of having energy drinks on hypercalcaemia. In: 16th International Conference on Computer and Information Technology (ICCIT), pp. 109–114. IEEE (2014)Google Scholar
  20. 20.
    Shouldice, R., Ward, S., O’Brien, L.M., O’Brien, C., Redmond, S., Gozal, D., Heneghan, C.: PR and PP ECG interval variation during obstructive apnea and hypopnea. In: Proceedings of the IEEE 30th Annual Northeast Bioengineering Conference, pp. 100–101. IEEE (2004)Google Scholar
  21. 21.
    Mukhopadhyay, S. K., Mitra, M., Mitra, S.: An ECG data compression method via R-peak detection and ASCII character encoding. In: 2011 International Conference on Computer, Communication and Electrical Technology (ICCCET), pp. 136–141. IEEE (2011)Google Scholar
  22. 22.
    Aram, Z., Setarehdan, S.K.: RR interval simulation based on power spectrum curve fitting. In: 2013 20th Iranian Conference on Biomedical Engineering (ICBME), pp. 132–136. IEEE (2013)Google Scholar
  23. 23.
    Gregg, R.E., Babaeizadeh, S., Feild, D.Q., Helfenbein, E.D., Lindauer, J.M., Zhou, S.H.: Comparison of two automated methods for QT interval measurement. Comput. Cardiol. 34, 427–430(2007) (IEEE)Google Scholar
  24. 24.
    He, J., Kryger, M.H., Zorick, F.J., Conway, W., Roth, T.: Mortality and apnea index in obstructive sleep apnea. Experience in 385 male patients. FREE TO VIEW. Chest 94(1), 9–14 (1988)CrossRefGoogle Scholar

Copyright information

© Springer India 2016

Authors and Affiliations

  • Mridu Sahu
    • 1
  • Saransh Shirke
    • 2
  • Garima Pathak
    • 1
  • Prashant Agarwal
    • 1
  • Ravina Gupta
    • 1
  • Vishal Sodhi
    • 1
  • N. K. Nagwani
    • 3
  • Shrish Verma
    • 4
  1. 1.Department of Information TechnologyNIT RaipurRaipurIndia
  2. 2.Department of Electrical EngineeringNIT RaipurRaipurIndia
  3. 3.Department of Computer Science EngineeringNIT RaipurRaipurIndia
  4. 4.Department of Electronics and TelecommunicationNIT RaipurRaipurIndia

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