Evaluation of a New mHealth Tympanometer

Plain-language summary

Children in rural and underserved communities experience a disproportionately high burden of infection-related hearing loss, which is often preventable with timely identification and follow-up care. A tympanometer is a device that evaluates the health of the middle ear but is often not used in screening programs due to barriers of high cost and need for trained professionals such as audiologists to use the device. To address these barriers, a low cost, lay friendly, mobile health (mHealth) prototype tympanometer has been developed. In addition, a machine learning (ML) algorithm has been designed to guide lay users to interpret tympanometer results, overcoming the need for audiologists. Broad implementation of the lay friendly tympanometer and ML algorithm will transform screening in areas where prevalence of infection-related hearing loss is high, and access to specialty care is limited. In this study the prototype mHealth tympanometer will be evaluated against commercial tympanometry. It will be used by audiologists, an essential step before testing the performance of the device with lay users. Approximately 20 adult patients and 10 pediatric patients with various middle ear pathologies will be enrolled in the study, with the goal of obtaining 60 ears with data from both the prototype and commercial tympanometers. Audiologists will obtain tympanometry measurements on both ears of each participant and interpret the results, first with the prototype device and then with the commercial tympanometer that is typically used during a clinical evaluation. Tympanometry interpretation will include classification into one of 3 categories (Type A, B, or C). Agreement in results between the prototype and commercial devices will be assessed. Agreement between audiologist interpretations and the ML algorithm from the prototype mHealth tympanometer will be assessed.

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