Joint Fourier and non-Fourier spectral / pseudo-spectral approach to the lung bioacoustics and biomedical signal fingerprinting as a way to increase the quality of the lung diagnostics using supercomplex hybridization of different DSP methodsстатья
Информация о цитировании статьи получена из
Web of Science
Дата последнего поиска статьи во внешних источниках: 20 апреля 2016 г.
Аннотация:A novel approach to the multifactor / multi-variance analysis of lung sounds has been developed and implemented into the experimental biomedical practice. This approach is based on the information decision, extracted from different spectral or pseudo-spectral analysis results, including non-Fourier spectra, Prony energy spectra, moving average spectra, autoregressive frequency spectra, minimum variance frequency spectra, eigenanalysis frequency estimation, Lomb periodograms, etc. The above approach reduces the degree of uncertainty of the analysis due to consideration of the additional diagnostic information derived from the standard raw data (files) of the pulmonary signal registration. The application of the novel complex mathematical methods of data processing allows for the first time to extract a number of important and complex descriptors which were previously ignored due to their complexity, but now can be easily interpreted using the novel data mining approaches.