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Detecting Sleep Apnea by Heart Rate Variability Analysis: Assessing the Validity of Databases and Algorithms

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Abstract

Obstructive sleep apnea (OSA) is a serious disorder caused by intermittent airway obstruction which may have dangerous impact on daily living activities. Heart rate variability (HRV) analysis could be used for diagnosing OSA, since this disease affects HRV during sleep. In order to validate different algorithms developed for detecting OSA employing HRV analysis, several public or proprietary data collections have been employed for different research groups. However, for validation purposes, it is obvious and evident the lack of a common standard database, worldwide recognized and accepted by the scientific community. In this paper, different algorithms employing HRV analysis were applied over diverse public and proprietary databases for detecting OSA, and the outcomes were validated in terms of a statistical analysis. Results indicate that the use of a specific database may strongly affect the performance of the algorithms, due to differences in methodologies of processing. Our results suggest that researchers must strongly take into consideration the database used when quoting their results, since selected cases are highly database dependent and would bias conclusions.

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Acknowledgments

The authors would like to thank Dr. Carlos Zamarrón for his help with the data acquisition for the CHUS data set. This work has been partially supported by the Consellería de Industria, Xunta de Galicia, under the grant PGIDIT06SIN30501PR and by the Spanish Ministry under the grant: TIN-2006-15460-C04-02.

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Authors and Affiliations

  1. Department of Computer Science, ESEI, University of Vigo, Campus As Lagoas, 32004, Ourense, Spain

    María J. Lado, Xosé A. Vila, Leandro Rodríguez-Liñares, Arturo J. Méndez & David N. Olivieri

  2. Department of Electronics and Computer Science, University of Santiago de Compostela, 15782, Santiago de Compostela, Spain

    Paulo Félix

Authors
  1. María J. Lado
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  2. Xosé A. Vila
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  3. Leandro Rodríguez-Liñares
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  4. Arturo J. Méndez
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  5. David N. Olivieri
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  6. Paulo Félix
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Correspondence to María J. Lado.

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Lado, M.J., Vila, X.A., Rodríguez-Liñares, L. et al. Detecting Sleep Apnea by Heart Rate Variability Analysis: Assessing the Validity of Databases and Algorithms. J Med Syst 35, 473–481 (2011). https://doi.org/10.1007/s10916-009-9383-5

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  • DOI: https://doi.org/10.1007/s10916-009-9383-5

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