PDF(Pubmed)
Abstract：
Assessing bladder function is pivotal in urological health, with bladder volume a critical indicator. Traditional devices, hindered by high costs and cumbersome sizes, are being increasingly supplemented by portable alternatives; however, these alternatives often fall short in measurement accuracy. Addressing this gap, this study introduces a novel A-mode ultrasound-based bladder volume estimation algorithm optimized for portable devices, combining efficient, precise volume estimation with enhanced usability. Through the innovative application of a wavelet energy ratio adaptive denoising method, the algorithm significantly improves the signal-to-noise ratio, preserving critical signal details amidst device and environmental noise. Ultrasonic echoes were employed to acquire positional information on the anterior and posterior walls of the bladder at several points, with an ellipsoid fitted to these points using the least squares method for bladder volume estimation. Ultimately, a simulation experiment was conducted on an underwater porcine bladder. The experimental results indicate that the bladder volume estimation error of the algorithm is approximately 8.3%. This study offers a viable solution to enhance the accuracy and usability of portable devices for urological health monitoring, demonstrating significant potential for clinical application.
摘要：
评估膀胱功能在泌尿系统健康中至关重要，膀胱容积是一个关键指标。传统设备,受到高成本和笨重尺寸的阻碍，越来越多地得到便携式替代品的补充；然而，这些替代方案通常在测量精度方面不足。解决这个差距，这项研究介绍了一种新颖的基于A型超声的膀胱体积估计算法，该算法针对便携式设备进行了优化，结合高效，精确的体积估计与增强的可用性。通过一种小波能量比自适应去噪方法的创新应用,该算法显著提高了信噪比，在设备和环境噪声中保留关键信号细节。超声回波被用来获取膀胱前壁和后壁在几个点上的位置信息，使用最小二乘法对这些点拟合的椭圆体进行膀胱容积估计。最终,在水下猪膀胱上进行了模拟实验。实验结果表明,该算法的膀胱容积估计误差约为8.3%。这项研究提供了一个可行的解决方案，以提高泌尿系统健康监测便携式设备的准确性和可用性，证明了临床应用的巨大潜力。
