… This paper presents the role of spectral analysis to differentiate between the wheezing of
asthma, pneumonia, and normal subjects. Respiratory signals are acquired by an electret …

… This study reveals that classification of asthmatic subjects during tidal breathing as mild,
moderate and severe can be performed using SI features. The findings also illustrate that the …

… and correct classification rates we can say that any spectral analysis method does not
work successfully for analyzing of right basal sounds belong to severe asthma. In addition, …

… of 15–75 Hz as suitable for the analysis of asthmatic severity. Subsequently, integrations of
the … Previous detailed power spectrum analysis have computed various other power statistical …

… analysed to classify different levels of asthma severity. Wheeze signals were obtained from
patients with three asthma severity levels, namely mild, moderate and severe asthma. The …

… asthma and non-asthma. The proposed method allows for automatic classification of asthma
and non-asthma … in real-time for assessment and management of the asthmatic conditions. …

… Complicated quantitative relationships between the respiration sound power spectrum and
the asthmatic state are likely to be established by computational techniques such as artificial …

… data was acquired on the entire detector range ie −32 to 1836 cm −1 but only the region
from 600–1700 cm −1 has been used for subsequent spectral analysis in this study. …

… spectral density (PSD), and fed to the artificial neural network (ANN) classifier for the 3-class
classification. … multiclass classification system achieves reasonable classification accuracy …

… taken from asthma and … spectral density function to the total area is 50 % and 90 %,
respectively. Ideally, ie for an accurate estimation of power spectral density, since the power spectral …