A Smartphone-Based System for Automated Bedside Detection of Crackle Sounds in Diffuse Interstitial Pneumonia Patients.

Bersain Reyes,Ramón González-Camarena,Tomas Aljama-Corrales,Mayra Mejía-Ávila,Nemecio Olvera-Montes,Sonia Charleston-Villalobos

doi:10.3390/s18113813

Abstract

In this work, we present a mobile health system for the automated detection of crackle sounds comprised by an acoustical sensor, a smartphone device, and a mobile application (app) implemented in Android. Although pulmonary auscultation with traditional stethoscopes had been used for decades, it has limitations for detecting discontinuous adventitious respiratory sounds (crackles) that commonly occur in respiratory diseases. The proposed app allows the physician to record, store, reproduce, and analyze respiratory sounds directly on the smartphone. Furthermore, the algorithm for crackle detection was based on a time-varying autoregressive modeling. The performance of the automated detector was analyzed using: (1) synthetic fine and coarse crackle sounds randomly inserted to the basal respiratory sounds acquired from healthy subjects with different signal to noise ratios, and (2) real bedside acquired respiratory sounds from patients with interstitial diffuse pneumonia. In simulated scenarios, for fine crackles, an accuracy ranging from 84.86% to 89.16%, a sensitivity ranging from 93.45% to 97.65%, and a specificity ranging from 99.82% to 99.84% were found. The detection of coarse crackles was found to be a more challenging task in the simulated scenarios. In the case of real data, the results show the feasibility of using the developed mobile health system in clinical no controlled environment to help the expert in evaluating the pulmonary state of a subject.

Highlights

Chronic respiratory diseases (CRDs) are among the principal causes of mortality and morbidity around the world, according to the World Health Organization [1]
A list with the sounds already recorded for that patient is displayed in the inferior portion of the app so that the user can select one to analyze it or can use a floating action button (FAB) to acquire a new respiratory sound recording
We proposed a smartphone-based CORSA system for the task of automated

Summary

Introduction

Chronic respiratory diseases (CRDs) are among the principal causes of mortality and morbidity around the world, according to the World Health Organization [1]. The first approach employed in the diagnosis of pulmonary diseases is the clinical examination of the pulmonary function that includes clinical history and auscultation of the lungs with the stethoscope. The stethoscope remains the most widely used instrument in clinical medicine and still guides diagnosis when other pulmonary function tests are not available, the auscultation by the stethoscope has several limitations, e.g., it is a subjective process that depends on the ability and expertise of the physician [2], Sensors 2018, 18, 3813; doi:10.3390/s18113813 www.mdpi.com/journal/sensors. Sensors 2018, 18, 3813 it is limited by human audition [3], the stethoscope may be more adequate for cardiac auscultation [4], and the lung sounds are not permanently recorded for further analysis.

Methods

Results

Conclusion