Detecting Middle Ear Fluid Using Smartphones

项目总结 中耳炎是发展中国家最常见的儿童疾病之一；它的许多并发症 如果及早发现中耳积液是可以预防的。我们提出了一个可访问的、准确的 基于智能手机的筛查工具，(I)使用智能手机向耳道发送柔和的声波啁啾 扬声器，(Ii)使用智能手机麦克风检测从耳膜反射的声音，以及(Iii)使用 机器学习模型对这些反射进行分类，并实时预测中耳积液状态。给定 智能手机的无处不在和视觉耳镜的不准确，我们提出的系统有可能成为 在发展中国家，医疗保健提供者和国内护理人员使用的默认筛查工具。

PROJECT SUMMARY Otitis media is one of the most common childhood diseases in developing countries; many of its complications are preventable if middle ear fluid is detected early. We propose an accessible and accurate smartphone-based screening tool that (i) sends a soft acoustic chirp into the ear canal using the smartphone speaker, (ii) detects reflected sound from the eardrum using the smartphone microphone, and (iii) employs a machine learning model to classify these reflections and predict middle ear fluid status in realtime. Given the ubiquity of smartphones and the inaccuracy of visual otoscopy, the system we propose has the potential to be the default screening tool used in developing countries by healthcare providers and caregivers at home.