A Smart Wearable Device for Monitoring Urination Function in Benign Prostatic Hyperplasia

Overview

Benign Prostatic Hyperplasia (BPH) is a common condition that can cause bothersome urination problems and reduce quality of life. Accurately measuring how the bladder empties is important for diagnosis and treatment, but current methods like uroflowmetry can be inconvenient and are done only at a clinic. This study aims to test a new, non-invasive smart wearable device that uses Electrical Impedance Tomography (EIT) to monitor bladder function in patients with BPH. The device is worn on the lower abdomen. In this study, participants will use this EIT device while also undergoing the standard uroflowmetry test. The main goal is to see how well the measurements from the new device (like urine flow rate and volume) agree with those from the standard test. The study hopes to show that this wearable device can accurately and comfortably track bladder function over time. If successful, it could lead to a new tool for doctors to better monitor patients with BPH, even potentially at home.

Background: Benign Prostatic Hyperplasia (BPH) is a prevalent cause of Lower Urinary Tract Symptoms (LUTS). Current objective assessment tools like uroflowmetry have limitations, including single-point measurement and the need for a clinical setting. Electrical Impedance Tomography (EIT) is a non-invasive, radiation-free imaging technique that shows promise for dynamic, real-time monitoring of internal organs. Preliminary work by our team has developed a wearable EIT system capable of 3D reconstruction. Objectives: The primary objective is to evaluate the accuracy and agreement of the EIT wearable device in determining key uroflowmetry parameters (maximum flow rate, average flow rate, voided volume) against traditional uroflowmetry as the reference standard. Secondary objectives include assessing its capability for dynamic bladder volume monitoring and exploring an AI-based analysis framework. Study Design: This is a single-center, self-controlled, diagnostic consistency trial. Inclusion criteria: 1. Patients with BPH who need urodynamic tests to further evaluate the underlying pathophysiology of LUTS prior to invasive treatment. 2. Patients who understand and agree with the written informed consent, and voluntary to participate in the study. . Key exclusion criteria： 1. Patients with catheter-dependent urinary retention. 2. Patients who cannot void \> 150ml. 3. Patients with uncontrolled acute urinary tract infections. 4. Patients who suffer from severe mental illness or other diseases that may affect judgment or cooperation during the study. 5. Patients with implanted cardiac pacemaker or other electronic implants that may potentially be interfered by the EIT device. 6. Patients with other conditions who are deemed unsuitable for participation by the investigator. Interventions: Eligible participants will wear the EIT electrode array on the lower abdomen. After baseline emptying and controlled water ingestion, the EIT device will continuously monitor the filling phase until a strong urge to void. Participants will then void into a standard uroflowmeter, with the EIT device simultaneously recording the voiding process. Primary Outcome: The agreement between EIT-reconstructed and uroflowmetry data during voiding, measured by temporal alignment error for key parameters and overall curve similarity. Secondary Outcomes: Agreement under different bladder volumes, and subject acceptance via a comfort questionnaire. Statistical Methods: Statistical analyses will be performed using R software version 4.5.1. Measurement data following a normal or approximately normal distribution will be expressed as mean ± standard deviation (x±s), and intergroup comparisons will use appropriate parametric tests (e.g., paired t-test for within-subject comparisons); data not meeting normality assumptions will be expressed as median (interquartile range) and analyzed using non-parametric tests (e.g., Wilcoxon signed-rank test). Agreement for continuous parameters (e.g., Qmax, VV) will be assessed using Bland-Altman plots with 95% limits of agreement and Intraclass Correlation Coefficient (ICC). Curve similarity will be assessed using methods such as Dynamic Time Warping (DTW) distance and Pearson correlation. A P-value \< 0.05 will be considered statistically significant.