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try. This correlation gave relevant information to
detect respiratory obstructed areas.
As verified only the right areas of the lung had
correlation with the wheezes parameters, which can
be explained by the fact of the majority of partici-
pants enrolled (n=5) presented with right lung infec-
tion. Nevertheless, the small sample size (6 partici-
pants with LRTI), limits and decrease the statistical
power and may have polarised the results.
Currently, there is a lack of published data as-
sessing the correlation between wheeze and spi-
rometry parameters and therefore, it is believed that
these findings provide a significant contribution for
research and clinical practice.
5 CONCLUSIONS
This study suggests that the TF-WD algorithm is a
robust method for computerised wheeze detection in
patients with LRTI. Furthermore, the use of compu-
terised auscultation and spirometry as outcome
measures to detect the area of obstruction in patients
with this respiratory condition is also supported.
However, further studies with larger samples are
needed to fully confirm the presented results.
ACKNOWLEDGEMENTS
The authors gratefully acknowledge the funding
provided to the project “Adventitious lung sounds as
indicators of severity and recovery of lung pathology
and sputum location- PTDC/SAU-
BEB/101943/2008” by Fundação para a Ciência e a
Tecnologia (FCT). The authors would also like to
thank to Vânia Rocha for contributing to the annota-
tion process.
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