Detecting middle ear fluid using smartphones
Detecting middle ear fluid using smartphones
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DOI：
10.1126/scitranslmed.aav1102
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发表时间：
2019-05-15
影响因子：
17.1
通讯作者：
Gollakota, Shyamnath
中科院分区：
文献类型：
--
作者：
Chan, Justin;Raju, Sharat;Gollakota, Shyamnath
中耳积液的存在是两种最常见的小儿耳部疾病的关键诊断标志：急性中耳炎和渗出性中耳炎。我们提出了一种可访问的解决方案，该解决方案使用现有智能手机中的扬声器和麦克风，通过评估鼓膜移动性来检测中耳液。我们在一家小儿外科中心对98例患者的耳朵进行了临床研究。使用留一交叉验证来估计未知数据的性能，我们获得了基于智能手机的机器学习算法的曲线下面积（AUC）为0.898。相比之下，需要定制硬件的商业声反射仪实现了0.776的AUC。此外，我们达到了85%的灵敏度和82%的特异性，与已发表的鼓室测压和气动耳镜检查的性能指标相当。在多个智能手机平台上进行测试时，也获得了类似的结果。儿科患者的父母（n = 25耳）在使用基于智能手机的系统时表现出与经过培训的临床医生相似的性能。这些结果表明，智能手机有可能成为检测中耳液存在的低屏障和有效的筛查工具。
The presence of middle ear fluid is a key diagnostic marker for two of the most common pediatric ear diseases: acute otitis media and otitis media with effusion. We present an accessible solution that uses speakers and microphones within existing smartphones to detect middle ear fluid by assessing eardrum mobility. We conducted a clinical study on 98 patient ears at a pediatric surgical center. Using leave-one-out cross-validation to estimate performance on unseen data, we obtained an area under the curve (AUC) of 0.898 for the smartphone-based machine learning algorithm. In comparison, commercial acoustic reflectometry, which requires custom hardware, achieved an AUC of 0.776. Furthermore, we achieved 85% sensitivity and 82% specificity, comparable to published performance measures for tympanometry and pneumatic otoscopy. Similar results were obtained when testing across multiple smartphone platforms. Parents of pediatric patients (n = 25 ears) demonstrated similar performance to trained clinicians when using the smartphone-based system. These results demonstrate the potential for a smartphone to be a low-barrier and effective screening tool for detecting the presence of middle ear fluid.