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Corrected Integral Shape Averaging Applied to Obstructive Sleep Apnea Detection from the Electrocardiogram

Abstract

We present a technique called corrected integral shape averaging (CISA) for quantifying shape and shape differences in a set of signals. CISA can be used to account for signal differences which are purely due to affine time warping (jitter and dilation/compression), and hence provide access to intrinsic shape fluctuations. CISA can also be used to define a distance between shapes which has useful mathematical properties; a mean shape signal for a set of signals can be defined, which minimizes the sum of squared shape distances of the set from the mean. The CISA procedure also allows joint estimation of the affine time parameters. Numerical simulations are presented to support the algorithm for obtaining the CISA mean and parameters. Since CISA provides a well-defined shape distance, it can be used in shape clustering applications based on distance measures such as-means. We present an application in which CISA shape clustering is applied to P-waves extracted from the electrocardiogram of subjects suffering from sleep apnea. The resulting shape clustering distinguishes ECG segments recorded during apnea from those recorded during normal breathing with a sensitivity of and specificity of.

References

  1. Ramsay JO, Silverman BW: Functional Data Analysis, Springer Series in Statistics. Springer, New York, NY, USA; 1997.

    Book  Google Scholar 

  2. Boudaoud S, Rix H, Meste O: Integral shape averaging and structural average estimation: a comparative study. IEEE Transactions on Signal Processing 2005,53(10):3644-3650.

    Article  MathSciNet  Google Scholar 

  3. Boudaoud S, Rix H, Meste O: Providing sample shape statistics with FCA and ISA approaches. Proceedings of the 13th Workshop on Statistical Signal Processing (SSP '05), July 2005, Bordeaux, France 443–448.

    Google Scholar 

  4. Rix H, Meste O, Muhammad W: Averaging signals with random time shift and time scale fluctuations. Methods of Information in Medicine 2004,43(1):13-16.

    Article  Google Scholar 

  5. Rix H, Malengé JP: detecting small variations in shape. IEEE Transactions on Systems, Man, and Cybernetics 1980,10(1):90-96.

    MathSciNet  Google Scholar 

  6. Rix H, Boudaoud S, Meste O: Clustering signal shapes: applications to P-waves in ECG. Proceedings of the 2nd European Medical and Biological Engineering Conference (EMBEC '02), December 2002, Vienna, Austria 364–365.

    Google Scholar 

  7. Boudaoud S, Rix H, Blanc JJ, Cornily JC, Meste O: Integrated shape averaging of the P-wave applied to AF risk detection. Proceedings of the 30th Annual International Conference of Computers in Cardiology, September 2003, Thessaloniki, Greece 30: 125–128.

    Google Scholar 

  8. Boudaoud S, Heneghan C, Rix H, Meste O, O'Brien C: P-wave shape changes observed in the surface electrocardiogram of subjects with obstructive sleep apnoea. Proceedings of the 32nd Annual International Conference on Computers in Cardiology, September 2005, Lyon, France 359–362.

    Google Scholar 

  9. Young T, Evans L, Finn L, Palta M: Estimation of the clinically diagnosed proportion of sleep apnea syndrome in middle-aged men and women. Sleep 1997,20(9):705-706.

    Article  Google Scholar 

  10. Shamsuzzaman ASM, Gersh BJ, Somers VK: Obstructive sleep apnea: implications for cardiac and vascular disease. Journal of the American Medical Association 2003,290(14):1906-1914. 10.1001/jama.290.14.1906

    Article  Google Scholar 

  11. Leung RST, Bradley TD: Sleep apnea and cardiovascular disease. American Journal of Respiratory and Critical Care Medicine 2001,164(12):2147-2165.

    Article  Google Scholar 

  12. Penzel T, McNames J, de Chazal P, Raymond B, Murray A, Moody G: Systematic comparison of different algorithms for apnoea detection based on electrocardiogram recordings. Medical and Biological Engineering and Computing 2002,40(4):402-407. 10.1007/BF02345072

    Article  Google Scholar 

  13. Ramsay JO, Li X: Curve registration. Journal of the Royal Statistical Society. Series B 1998,60(2):351-363. 10.1111/1467-9868.00129

    Article  MathSciNet  Google Scholar 

  14. Gervini D, Gasser T: Self-modelling warping functions. Journal of the Royal Statistical Society. Series B 2004,66(4):959-971. 10.1111/j.1467-9868.2004.B5582.x

    Article  MathSciNet  Google Scholar 

  15. Lawton WH, Sylvestre EA, Maggio MS: Self modeling non linear regression. Technometrics 1972,14(3):513-532. 10.2307/1267281

    Article  Google Scholar 

  16. Jain AK, Duin RPW, Mao J: Statistical pattern recognition: a review. IEEE Transactions on Pattern Analysis and Machine Intelligence 2000,22(1):4-37. 10.1109/34.824819

    Article  Google Scholar 

  17. Carlson J, Johansson R, Olsson SB: Classification of electrocardiographic P-wave morphology. IEEE Transactions on Biomedical Engineering 2001,48(4):401-405. 10.1109/10.915704

    Article  Google Scholar 

  18. Dilaveris PE, Gialafos JE: Future concepts in P-wave morphological analyses. Cardiac Electrophysiology Review 2002,6(3):221-224. 10.1023/A:1016320807103

    Article  Google Scholar 

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://doi.org/creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Boudaoud, S., Rix, H., Meste, O. et al. Corrected Integral Shape Averaging Applied to Obstructive Sleep Apnea Detection from the Electrocardiogram. EURASIP J. Adv. Signal Process. 2007, 032570 (2007). https://doi.org/10.1155/2007/32570

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  • DOI: https://doi.org/10.1155/2007/32570

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