Faculty of Medicine, Saint Joseph University, Beirut, Lebanon.
College of Engineering and Technology, American University of the Middle East, Egaila, Kuwait.
Sci Rep. 2021 May 27;11(1):11250. doi: 10.1038/s41598-021-90659-9.
Uroflowmetry (UF) is a common clinic-based non-invasive test to diagnose Lower Urinary Tract Dysfunction (LUTD). Accurate home-based uroflowmetry methods are needed to conveniently conduct repeated uroflowmetries when patients are physiologically ready to urinate. To this end, we propose and evaluate a novel mobile sonouroflowmetry (SUF) method that estimates the urinary flow rate from a sound signal recorded using a mobile phone. By linearly mapping the total sound energy to the total voided volume, the sound energy curve is transformed to a flow rate curve allowing the estimation of the flow rate over time. An evaluation using data from 44 healthy young men showed high similarity between the UF and SUF flow rates with a mixed-effects model correlation coefficient of 0.993 and a mean root mean square error of 2.37 ml/s. Maximum flow rates were estimated with an average absolute error of 2.41 ml/s. Future work on mobile uroflowmetry can use these results as an initial benchmark for flow rate estimation accuracy.
尿流率测定(UF)是一种常见的基于临床的非侵入性测试,用于诊断下尿路功能障碍(LUTD)。需要准确的基于家庭的尿流率测定方法,以便在患者生理上准备好排尿时方便地进行重复尿流率测定。为此,我们提出并评估了一种新的移动超声尿流率测定(SUF)方法,该方法通过使用手机记录的声音信号来估计尿流率。通过将总声能线性映射到总排空量,将声能曲线转换为流速曲线,从而可以随时间估计流速。使用来自 44 名健康年轻男性的数据进行评估表明,UF 和 SUF 流速之间具有很高的相似性,混合效应模型相关系数为 0.993,平均均方根误差为 2.37ml/s。最大流量的平均绝对误差为 2.41ml/s。未来的移动尿流率研究可以将这些结果用作流量估计准确性的初始基准。