An Online Peak Extraction Algorithm for Ion Mobility Spectrometry Data

  • Dominik Kopczynski
  • Sven Rahmann
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8701)


Ion mobility (IM) spectrometry (IMS), coupled with multi-capillary columns (MCCs), has been gaining importance for biotechnological and medical applications because of its ability to measure volatile organic compounds (VOC) at extremely low concentrations in the air or exhaled breath at ambient pressure and temperature. Ongoing miniaturization of the devices creates the need for reliable data analysis on-the-fly in small embedded low-power devices. We present the first fully automated online peak extraction method for MCC/IMS spectra. Each individual spectrum is processed as it arrives, removing the need to store a whole measurement of several thousand spectra before starting the analysis, as is currently the state of the art. Thus the analysis device can be an inexpensive low-power system such as the Raspberry Pi.

The key idea is to extract one-dimensional peak models (with four parameters) from each spectrum and then merge these into peak chains and finally two-dimensional peak models. We describe the different algorithmic steps in detail and evaluate the online method against state-of-the-art peak extraction methods using a whole measurement.


Volatile Organic Compound Online Algorithm Drift Time Cosine Similarity Inverse Gaussian Distribution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Bessa, V., Darwiche, K., Teschler, H., Sommerwerck, U., Rabis, T., Baumbach, J.I., Freitag, L.: Detection of volatile organic compounds (VOCs) in exhaled breath of patients with chronic obstructive pulmonary disease (COPD) by ion mobility spectrometry. International Journal for Ion Mobility Spectrometry 14, 7–13 (2011)CrossRefGoogle Scholar
  2. 2.
    Bödeker, B., Vautz, W., Baumbach, J.I.: Peak finding and referencing in MCC/IMS-data. International Journal for Ion Mobility Spectrometry 11(1), 83–87 (2008)CrossRefGoogle Scholar
  3. 3.
    Bunkowski, A.: MCC-IMS data analysis using automated spectra processing and explorative visualisation methods. Ph.D. thesis, University Bielefeld: Bielefeld, Germany (2011)Google Scholar
  4. 4.
    Bunkowski, A., Bödeker, B., Bader, S., Westhoff, M., Litterst, P., Baumbach, J.I.: MCC/IMS signals in human breath related to sarcoidosis – results of a feasibility study using an automated peak finding procedure. Journal of Breath Research 3(4), 046001 (2009)Google Scholar
  5. 5.
    D’Addario, M., Kopczynski, D., Baumbach, J.I., Rahmann, S.: A modular computational framework for automated peak extraction from ion mobility spectra. BMC Bioinformatics 15(1), 25 (2014)CrossRefGoogle Scholar
  6. 6.
    Dempster, A.P., Laird, N.M., Rubin, D.B.: Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society. Series B (Methodological), 1–38 (1977)Google Scholar
  7. 7.
    Eiceman, G.A., Karpas, Z.: Ion Mobility Spectrometry, 2 ed. Taylor & Francis (2005)Google Scholar
  8. 8.
    Einstein, A.: Über die von der molekularkinetischen Theorie der Wärme geforderte Bewegung von in ruhenden Flüssigkeiten suspendierten Teilchen. Annalen der Physik 322(8), 549–560 (1905)CrossRefGoogle Scholar
  9. 9.
    Ewing, R.G., Atkinson, D.A., Eiceman, G.A., Ewing, G.J.: A critical review of ion mobility spectrometry for the detection of explosives and explosive related compounds. Talanta 54(3), 515–529 (2001)CrossRefGoogle Scholar
  10. 10.
    Hauschild, A.C., Kopczynski, D., D’Addario, M., Baumbach, J.I., Rahmann, S., Baumbach, J.: Peak detection method evaluation for ion mobility spectrometry by using machine learning approaches. Metabolites 3(2), 277–293 (2013)CrossRefGoogle Scholar
  11. 11.
    Keller, T., Schneider, A., Tutsch-Bauer, E., Jaspers, J., Aderjan, R., Skopp, G.: Ion mobility spectrometry for the detection of drugs in cases of forensic and criminalistic relevance. Int. J. Ion Mobility Spectrom 2(1), 22–34 (1999)Google Scholar
  12. 12.
    Kolehmainen, M., Rönkkö, P., Raatikainen, O.: Monitoring of yeast fermentation by ion mobility spectrometry measurement and data visualisation with self-organizing maps. Analytica Chimica Acta 484(1), 93–100 (2003)CrossRefGoogle Scholar
  13. 13.
    Kopczynski, D., Baumbach, J., Rahmann, S.: Peak modeling for ion mobility spectrometry measurements. In: 2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO), pp. 1801–1805. IEEE (August 2012)Google Scholar
  14. 14.
    Kopczynski, D., Rahmann, S.: Using the expectation maximization algorithm with heterogeneous mixture components for the analysis of spectrometry data. Pre-print - CoRR abs/1405.5501 (2014)Google Scholar
  15. 15.
    Kreuder, A.E., Buchinger, H., Kreuer, S., Volk, T., Maddula, S., Baumbach, J.: Characterization of propofol in human breath of patients undergoing anesthesia. International Journal for Ion Mobility Spectrometry 14, 167–175 (2011)CrossRefGoogle Scholar
  16. 16.
    Munteanu, A., Wornowizki, M.: Demixing empirical distribution functions. Tech. Rep. 2, TU Dortmund (2014)Google Scholar
  17. 17.
    Needleman, S.B., Wunsch, C.D.: A general method applicable to the search for similarities in the amino acid sequence of two proteins. Journal of Molecular Biology 48(3), 443–453 (1970)CrossRefGoogle Scholar
  18. 18.
    Nocedal, J., Wright, S.J.: Numerical Optimization, 2nd edn. Springer, New York (2006)zbMATHGoogle Scholar
  19. 19.
    Spangler, G.E., Collins, C.I.: Peak shape analysis and plate theory for plasma chromatography. Analytical Chemistry 47(3), 403–407 (1975)CrossRefGoogle Scholar
  20. 20.
    Westhoff, M., Litterst, P., Freitag, L., Urfer, W., Bader, S., Baumbach, J.: Ion mobility spectrometry for the detection of volatile organic compounds in exhaled breath of lung cancer patients. Thorax 64, 744–748 (2009)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Dominik Kopczynski
    • 1
    • 2
  • Sven Rahmann
    • 1
    • 2
    • 3
  1. 1.Collaborative Research Center SFB 876TU DortmundGermany
  2. 2.Bioinformatics, Computer Science XITU DortmundGermany
  3. 3.Genome Informatics, Institute of Human Genetics, Faculty of MedicineUniversity Hospital Essen, University of Duisburg-EssenGermany

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