Diagnosis of pneumonia from sounds collected using low cost cell phones

Song, Insu (2015) Diagnosis of pneumonia from sounds collected using low cost cell phones. In: Proceedings of the International Joint Conference on Neural Networks. pp. 1-8. From: IJCNN 2015: International Joint Conference on Neural Networks, 12-17 July 2015, Killarney, Ireland.

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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.

Item ID: 39691
Item Type: Conference Item (Research - E1)
ISSN: 2161-4393
Keywords: mobile diagnosis, rapid-diagnosis, respiratory problem, lung sound, pneumonia, KNN, SVM
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Funders: Bill and Melinda Gates Foundation
Projects and Grants: Grand Challenges Explorations Initiative (OPP1032125)
Date Deposited: 02 Jun 2016 01:42
FoR Codes: 10 TECHNOLOGY > 1004 Medical Biotechnology > 100402 Medical Biotechnology Diagnostics (incl Biosensors) @ 50%
08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining @ 50%
SEO Codes: 92 HEALTH > 9202 Health and Support Services > 920203 Diagnostic Methods @ 100%
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