Abstract
This paper briefly summarizes results of recent research concerning the development of efficient, fast and robust methods for remote wheeze detection in patients with asthma. For the first time such a large collection of different approaches is compared in a single place, including signal tonality descriptors for asthma monitoring used in literature (such as kurtosis and spectral peaks entropy) and proposed in the authors’ previous works (such as tonal index (TI), spectral flatness, energy ratio, peak-to-mean ratio, correlation function (CF) and EVD-based descriptors, and linear-prediction error). It has been demonstrated using synthetic signals and real recordings that using TI and CF in combination results in the highest asthma wheeze detection efficiency among all tested methods.
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Wisniewski, M., Zielinski, T.P. (2012). Fast and Robust Method for Wheezes Recognition in Remote Asthma Monitoring. In: Piętka, E., Kawa, J. (eds) Information Technologies in Biomedicine. Lecture Notes in Computer Science(), vol 7339. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31196-3_57
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DOI: https://doi.org/10.1007/978-3-642-31196-3_57
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