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A smart stethoscope puts AI in medics’ ears

February 18, 2019

Our mission sprang from an ambitious global study of pneumonia that began in 2008, with funding from the Gates Foundation. The Pneumonia Etiology Research for Child Health (PERCH) study explored the causes of pediatric pneumonia across multiple countries in Africa, Asia, and South America.

In the course of this study, a team of doctors from Johns Hopkins set out to determine just how useful lung sounds could be in diagnosing pneumonia. At first, the researchers equipped local health workers with commercially available stethoscopes that they had augmented with small digital recorders. The health workers recorded lung sounds from the children they encountered in rural clinics and urban hospitals, then transmitted the files to expert pulmonologists at Johns Hopkins, who listened to these sounds and offered more informed medical opinions.

Quickly, the use of the commercial stethoscope became problematic. To get a decent recording from the lungs, the health worker had to position the device’s chest piece in just the right places on the child’s chest and back. Unfortunately, the local workers typically had only basic training in how to use the tool, and often missed the “sweet spots” that best transfer the lung sounds to the stethoscope head. Furthermore, they were usually making their recordings in noisy settings, nothing like the quiet doctor’s office for which the stethoscope is intended. Background sounds of people, machines, cars, and motorcycles would mix with the lung sounds, leaving the expert with a recording of cacophony. In addition, the local workers needed Internet access to transmit their files, and connectivity limitations and glitches meant that it often took many hours or even days to get back an expert diagnosis.

If they wanted to get useful recordings, the Johns Hopkins doctors decided, they’d have to entirely rethink the stethoscope. So they approached the university’s department of electrical and computer engineering, where one of us (West) is a professor, and the other (Elhilali) is an associate professor. As both of us specialize in audio engineering, we were eager to take up the challenge.

— Mounya Elhilali and James West
Johns Hopkins University


Read the full story in IEEE Spectrum >>

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