The goal of this project is to further develop an existing smart stethoscope in order to be capable of monitoring pediatric patients at home who suffer from asthma. Lung diseases impose a serious burden on healthcare systems, individuals and governments. WHO recognizes asthma as the leading chronic disease in children and estimates that 235 million people suffer from the disease worldwide, with over 380,000 deaths from the disease in 2015. In the United States, asthma prevalence and disease burden disproportionately affect Blacks or African-Americans compared with White Americans. From 2008 to 2010, the annual US asthma prevalence (11.9% for Black Americans versus 8.1% in Caucasians), mortality rate (0.23 versus 0.13 per 1000 patients per year), and emergency department visits (18.4 versus 6.1 visits per 100 patients per year) were all worse among Blacks or African-Americans. The fundamental causes of health disparities in relation to asthma are well understood (urban air pollution, housing, poor diet, poverty, and social and/or geographical isolation) but remain very difficult to solve. Early technological and mobile applications for remote management have attempted to address these problems, with somewhat positive results, but require patient self-assessment and do not include objective monitoring of lung status. A small number of wheeze detectors and pulmonary monitors have been approved for marketing by the FDA, but face several technological limitations and are not commercially available in the US. We reasoned that a long-term monitoring solution that can be used in the home by untrained patients, or family members of patients, could detect and monitor severity of airway inflammation in patients, provide insight into reasons for worsening or improved symptoms, provide tailored educational content and direct patients to medical follow before the situation becomes acute, thus reducing trips to emergency departments and readmission rates to hospitals. We find that several challenges exist when considering long term auscultatory monitoring solutions in non-traditional clinical settings: (1) unpredictable ambient noise, (2) the need for medical expertise to interpret lung sounds, (3) subjectivity in the analysis, and (4) difficulty using and placing the stethoscope. In order to overcome many of these challenges, the research team developed a smart stethoscope that was originally intended for use in low-resource countries by community health workers to differentiate between pediatric patients with crackles and wheezes. This smart stethoscope address all the challenges above by including (1) adaptive noise suppression that has been objectively and subjectively proven to be superior in all types of noise environments than traditional or other electronic stethoscopes, (2) on-board analysis algorithms that can detect crackles and wheezes in pediatric patients with an accuracy that matches that of a specialist, and (3) a uniform pickup surface that removes the requirement for exact placement of the device to get an accurate recording. In this project, we will validate that the device can be correctly used by parents of children with asthma through monitoring over a 6-week period following an ED visit through daily recordings. We then plan to confirm that our existing detection algorithms can be used or modified to track changes in the lung sound severity, followed by correlating these algorithm outputs with patient reported outcomes and environmental data. Simultaneously, we will be using patient feedback to iterate on the device design to create a version that minority and underserved patients are comfortable using in their home.
This proposal aims to validate a smart auscultation device for home use and develop algorithms that can track changes in, and severity of, wheezes and lung sounds in order to monitor patients over long periods of time, improve the clinical relevance of home monitoring for timely interventions, and decrease hospital admissions. Current state of the art technology available to minority patients suffering from asthma is unable to intelligently monitor patients at home and no long-term monitoring solutions exist for these conditions, resulting in increases in emergency department visits, especially of underserved patient populations. The academic partner has developed a smart stethoscope that offers greatly improved audio fidelity in any type of noise environment, automated on-board analysis and detection algorithms of lung sounds, and increased ease of use. The small business partner is in the process of commercializing the device for clinical use by trained, professional personnel. Together, we are aiming to test whether the device can be reliably used by non-trained personnel for home use, develop algorithms that would provide metrics for monitoring trends and severities of lung sounds, and make this technology easily available to and usable by afflicted populations such that it can improve the long-term outcome for patients and decrease the burden on underserved groups.
