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Sokolov Oleksandr, Dobosz Krzysztof, Dreszer Joanna, Duch Włodzisław, Grzelak Sławomir, Komendziński Tomasz,Mikołajewski Dariusz, Piotrowski Tomasz, Świerkocka Małgorzata, Weber Piotr. Spirometry Data Analysis and Monitoring in Medical and Physiological Tests. Journal of Education, Health and Sport. 2015;5(3):35-46. ISSN 2391-8306. DOI: 10.5281/zenodo.16171 http://ojs.ukw.edu.pl/index.php/johs/article/view/2015%3B5%283%29%3A35-46 https://pbn.nauka.gov.pl/works/546923 http://dx.doi.org/10.5281/zenodo.16171 Formerly Journal of Health Sciences. ISSN 1429-9623 / 2300-665X. Archives 2011 – 2014 http://journal.rsw.edu.pl/index.php/JHS/issue/archive Deklaracja. Specyfika i zawartość merytoryczna czasopisma nie ulega zmianie. Zgodnie z informacją MNiSW z dnia 2 czerwca 2014 r., że w roku 2014 nie będzie przeprowadzana ocena czasopism naukowych; czasopismo o zmienionym tytule otrzymuje tyle samo punktów co na wykazie czasopism naukowych z dnia 31 grudnia 2014 r. The journal has had 5 points in Ministry of Science and Higher Education of Poland parametric evaluation. Part B item 1089. (31.12.2014). © The Author (s) 2015; This article is published with open access at Licensee Open Journal Systems of Kazimierz Wielki University in Bydgoszcz, Poland and Radom University in Radom, Poland Open Access. This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. This is an open access article licensed under the terms of the Creative Commons Attribution Non Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted, non commercial use, distribution and reproduction in any medium, provided the work is properly cited. This is an open access article licensed under the terms of the Creative Commons Attribution Non Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted, non commercial use, distribution and reproduction in any medium, provided the work is properly cited. The authors declare that there is no conflict of interests regarding the publication of this paper. Received: 20.01.2014. Revised 27.02.2015. Accepted: 12.03.2015. Spirometry Data Analysis and Monitoring in Medical and Physiological Tests Oleksandr Sokolov1, Krzysztof Dobosz1, Joanna Dreszer2, 4, Włodzisław Duch1, 4, Sławomir Grzelak3, Tomasz Komendziński2, 4, Dariusz Mikołajewski1, 4, 5, Tomasz Piotrowski1, 4, Małgorzata Świerkocka4, Piotr Weber1 1 Department of Informatics, Faculty of Physics, Astronomy and Informatics, Nicolaus Copernicus University, Torun, Poland 2 Faculty of Humanities, Nicolaus Copernicus University, Toruń, Poland 3 Faculty of Physics, Astronomy and Informatics, Nicolaus Copernicus University, Torun, Poland 4 Neurocognitive Laboratory, Centre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University, Toruń, Poland 5 Institute of Mechanics and Applied Computer Science, Kazimierz Wielki University, Bydgoszcz, Poland Corresponding author: prof. Oleksandr Sokolov Department of Informatics Faculty of Physics, Astronomy and Informatics Nicolaus Copernicus University ul. Grudziadzka 5, 87-100 Torun, Poland e-mail: osokolov@is.umk.pl Abstract Research on the computational breath analysis constitute important part of current challenges within the medical sciences, artificial intelligence, and biomedical engineering. Despite efforts of scientists and clinicians current results seem be not satisfying. Computational models of breath processes based e.g. on fuzzy logic may constitute another breakthrough in aforementioned area offering completing position to the current state of the art, both in the area of theoretical and experimental computational neuroscience, and clinical applications. Aim of the study was to find out whether is true if our new concept of intelligent breath analysis system can constitute another step toward better analysis and understanding of the aforementioned processes. Keywords: breath measure; computational breath analysis; breath disorders; computational models; artificial intelligence. |
