Diagnosis of pneumonia from sounds collected using low cost cell phones

Respiratory diseases, such as pneumonia, cold, flu, and bronchitis, are still the leading causes of child mortality in the world. One solution for alleviating this problem is developing affordable respiratory-health assessment methods using computerized respiratory-sound analysis. This approach has become an active research area due to the recent developments of electronic recording devices, such as electronic stethoscopes. However, all existing methods require specialized equipment, which can be operated only by trained medical personals. We develop a low-cost cell phone-based rapid diagnosis method for respiratory health problems. A total of 367 breath sounds are collected from children's hospitals in order to develop accurate diagnosis models and evaluation. An extensive analysis is performed on the breath sounds. Statistically significance features are selected for each age group using ANOVA from 1197 acoustic features. The model is evaluated on a binary classification task: pneumonia vs. non-pneumonia. The results showed that the proposed method was able to effectively classify pneumonia even in the presence of environmental noises. The method achieved 91.98% accuracy with 92.06% sensitivity and 90.68% specificity. The results indicate that breath sounds recorded using low-cost mobile devices can be used to detect pneumonia effectively.