Key Laboratory for Micro/Nano Technology and System of Liaoning Province, Dalian University of Technology, Dalian 116024, China.
Sensors (Basel). 2024 Mar 20;24(6):1984. doi: 10.3390/s24061984.
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.
评估膀胱功能在泌尿系统健康中至关重要，膀胱容量是一个关键指标。传统的设备由于成本高和体积庞大，正逐渐被便携式设备所补充；然而，这些替代设备在测量精度上往往存在不足。为了解决这一差距，本研究引入了一种新型的基于 A 模式超声的膀胱容量估计算法，该算法针对便携式设备进行了优化，将高效、精确的容量估计与增强的易用性相结合。通过创新应用小波能量比自适应去噪方法，该算法显著提高了信号噪声比，在设备和环境噪声中保留了关键信号细节。超声回波被用于在几个点获取膀胱前壁和后壁的位置信息，然后使用最小二乘法将这些点拟合成一个椭球体，以进行膀胱容量估计。最终，在水下猪膀胱上进行了模拟实验。实验结果表明，该算法的膀胱容量估计误差约为 8.3%。本研究为提高便携式设备在泌尿系统健康监测中的准确性和易用性提供了可行的解决方案，具有显著的临床应用潜力。
