• Frontiers of Optoelectronics
  • Vol. 8, Issue 2, 183 (2015)
A. A. BULANOVA1、*, E. B. BUKREEVA1, Yu. V. KISTENEV1、2, and O. Yu. NIKIFOROVA3
Author Affiliations
  • 1Siberian State Medical University, Tomsk 634050, Russia
  • 2Tomsk State University, Tomsk 634050, Russia
  • 3V.E. Zuev Institute of Atmospheric Optics SB RAS, Tomsk 634055, Russia
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    DOI: 10.1007/s12200-015-0498-7 Cite this Article
    A. A. BULANOVA, E. B. BUKREEVA, Yu. V. KISTENEV, O. Yu. NIKIFOROVA. Diagnostics of bronchopulmonary diseases through Mahalanobis distance-based absorption spectral analysis of exhaled air[J]. Frontiers of Optoelectronics, 2015, 8(2): 183 Copy Citation Text show less
    References

    [1] Bukreeva E B, Bulanova A A, Kistenev Y V, Kuzmin D A, Tuzikov S A, Yumov E L. Analysis of the absorption spectra of gas emission of patients with lung cancer and chronic obstructive pulmonary disease by laser optoacoustic spectroscopy. In: Proceedings of SPIE 8699, Saratov Fall Meeting 2012: Optical Technologies in Biophysics and Medicine XIV; and Laser Physics and Photonics XIV. 2013, 86990K

    [2] 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, 2011, 14(1): 7–13

    [3] Van Berkel J J B N, Dallinga J W, M ller G M, Godschalk R W L, Moonen E J, Wouters E F M, Van Schooten F J. A profile of volatile organic compounds in breath discriminates COPD patients from controls. Respiratory Medicine, 2010, 104(4): 557–563

    [4] Phillips C O, Syed Y, Parthaláin N M, Zwiggelaar R, Claypole T C, Lewis K E. Machine learning methods on exhaled volatile organic compounds for distinguishing COPD patients from healthy controls. Journal of Breath Research, 2012, 6(3): 036003

    [5] Boshier P R, Mistry V, Cushnir J R, Curtis S, Elkin S, Kon O M, Marczin N, Hanna G B. Analysis of volatile biomarkers within exhaled breath for the diagnosis of pneumonia. Thorax, 2010, 65 (Suppl 4): A58–A59

    [6] Ageev B G, Kistenjov J V, Nekrasov E V, Nikiforova O J, Nikotin E S, Nikotina G S, Ponomarjov J N, Urazova O I, Filinjuk O V, Fokin V A, Janova G V. Estimate of expired air samples of patients with the pulmonary tuberculosis using laser photoacoustic spectroscopy technique. Bulletin of Siberian Medicine, 2012, 4: 116–120

    [7] Kharitonov S A, Barnes P J. Exhaled markers of pulmonary disease. American Journal of Respiratory and Critical Care Medicine, 2001, 163(7): 1693–1722

    [8] Intracavity laser opto-acoustic sensor ILPA-1. Passport. Technical description. Operating Instructions. Special Technologies, Ltd, Russia, Novosibirsk

    [9] Kistenev Y V, ed. Applications of laser spectroscopy and nonlinear analysis methods for investigation of medical-biological objects. Tomsk: TPU Ed., 2007

    A. A. BULANOVA, E. B. BUKREEVA, Yu. V. KISTENEV, O. Yu. NIKIFOROVA. Diagnostics of bronchopulmonary diseases through Mahalanobis distance-based absorption spectral analysis of exhaled air[J]. Frontiers of Optoelectronics, 2015, 8(2): 183
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