Abstract:
Respiratory sound signal analysis helps in distinguishing normal respiratory sounds
from abnormal respiratory sounds and this can be used to accurately diseases as is
done by a medical specialist via auscultation. A system capable of analyzing respiratory
sound can be very helpful in detection of pneumonia, asthma, tuberculosis, and heart
murmur sounds as the respiratory sound signal carries information about the underlying
physiology of the lungs and is used to detect presence of adventitious lung sounds
which are an indication of disease .This project attempts to diagnose pneumonia, by
using automated analysis of lung sounds. Such an approach minimizes the subjectivity
of diagnosis inherent to current practices by physicians. Breath sounds are recorded by
a physiological microphone and a stethoscope, and then analyzed in software using an
algorithm. The diagnosis is based on three techniques, first we get information about
patient and score the questions answered by the subject, and in second technique get the
lung sound, extract some specific features from lung sound and after feature extraction
make the decision based on the results of classification algorithm. At the same time the
system applies an algorithm on the breath sounds to calculate breaths per minute . After
executing this process make the decision based on the results of these steps.
