Optical method of diagnosing middle ear effusions

Otitis media (OM), or middle ear infections, is a common reason for clinical visits, with approximately 90% of children experiencing at least one episode. Diagnosing OM typically involves standard otoscopic examinations, which require significant expertise to distinguish between acute and chronic forms of OM or to detect the presence of fluid in the middle ear. Recently, advances in objective diagnostic methods, including artificial intelligence (AI) and machine learning (ML) algorithms, have shown promise in enhancing diagnostic accuracy. In this paper, we explore an alternative method known as speckle contrast imaging, which has the potential to identify subtle changes in the tympanic membrane or fluid accumulation within the middle ear. The quantitative nature of this technique, along with its relatively simple requirements, makes it a strong candidate for integration with machine learning algorithms. This could enable the development of a device suitable for at-home use by non-experts, including parents and caregivers. Once fully optimized, this approach can improve diagnostic accuracy, reduce unnecessary clinical visits, and minimize long-term complications associated with OM.