An intelligent wearable device based on electrical impedance tomography for dynamic and accurate monitoring of voiding function in patients with benign prostatic hyperplasia: protocol for a single-centre self-controlled diagnostic consistency study

Introduction

Benign prostatic hyperplasia (BPH) is the most common benign condition causing voiding dysfunction in middle-aged and elderly men, primarily manifesting as lower urinary tract symptoms (LUTS), including storage, voiding, and post-voiding symptoms (1,2). These symptoms can not only severely reduce the quality of life of patients but also lead to serious complications such as urinary retention, hydronephrosis, and bladder stones if the obstruction is not promptly addressed (3). With the accelerating trend of societal aging, the clinical diagnosis and treatment of BPH have become significant public health challenges in urology (4).

Accurate assessment of bladder storage and voiding function is crucial for the diagnosis, severity grading, and treatment decision-making (e.g., judging surgical indications) regarding BPH (5). Currently, clinicians rely on objective measures such as residual urine measurement, uroflowmetry, and urodynamic studies (UDS) (6). However, these existing monitoring methods have notable limitations: UDS is an invasive procedure carrying risks of infection and injury. Moreover, the unnatural medical environment can easily cause patient psychological stress, leading to distorted results (7,8). Ultrasound-based residual urine measurement is based on geometric assumptions, resulting in low accuracy and poor consistency and repeatability according to different operators. Furthermore, it is a static, instantaneous measurement incapable of dynamic continuous monitoring (9). Traditional uroflowmetry, being susceptible to environmental and psychological influences, fundamentally lacks the ability to provide synchronous information on bladder volume changes. Patient self-recorded voiding diaries suffer from poor compliance, especially among the elderly. Recent evidence has further highlighted the potential clinical relevance of uroflowmetry curve morphology and time-related parameters in patients with BPH and bladder outlet obstruction, supporting the need for monitoring approaches that can more comprehensively capture dynamic voiding characteristics (10).

Consequently, there is an urgent clinical need for an innovative technology capable of non-invasive, dynamic, accurate, and near-physiological monitoring of bladder function. Electrical impedance tomography (EIT) technology utilizes surface electrode arrays to measure the internal impedance distribution of biological tissues and reconstruct images (11,12), offering unique advantages such as being non-invasive, non-ionizing during monitoring, low-cost, portable, and suitable for real-time dynamic imaging. It has shown great potential in areas such as lung ventilation monitoring (13,14). The electric field relied upon for EIT imaging is a “soft field”, which naturally diverges into three-dimensional (3D) space, providing a theoretical basis for the 3D dynamic reconstruction of bladder volume and morphology changes.

Our research team has previously focused on the development and optimization of EIT technology, and we have innovatively created a high-performance EIT measurement system and high-resolution 3D reconstruction algorithms. Preliminary trials in healthy volunteers have indicated that the EIT-based monitoring device demonstrates good accuracy, repeatability, and generalizability in tracking dynamic bladder volume changes. We present this article in accordance with the SPIRIT reporting checklist (available at https://tau.amegroups.com/article/view/10.21037/tau-2026-1-0156/rc).

Methods

Trial design

This single-centre, self-controlled diagnostic consistency study is designed to evaluate whether the EIT wearable device can achieve clinically acceptable agreement and accuracy compared with standard uroflowmetry in key parameters including maximum flow rate (Qmax), average flow rate (Qave), and voided volume (VV). Each participant serves as their own control.

Participants

We plan to enroll 40 eligible patients with BPH from Peking University Third Hospital.

Inclusion criteria: (I) clinically diagnosed BPH requiring urodynamic evaluation to further assess the underlying pathophysiology of LUTS prior to invasive treatment; (II) ability to understand and provide written informed consent, and voluntary agreement to participate.

Exclusion criteria: (I) catheter-dependent urinary retention; (II) inability to void ≥150 mL; (III) uncontrolled acute urinary tract infection; (IV) severe mental illness or other conditions that may affect judgement or cooperation during the study; (V) presence of implanted cardiac pacemaker or other electronic implants that may potentially be interfered by the EIT device; (VI) any other condition deemed unsuitable for participation by the investigator.

Elimination criteria: (I) invalid or missing EIT or uroflowmetry data due to operational errors or other reasons during the experiment; (II) incomplete key demographic, imaging, or laboratory examination data; (III) decision by the investigator to terminate the subject’s participation for any other reason.

Study procedures

EIT intelligent wearable system

The system comprises a portable main unit (prototype), electrode array patches, and connecting cables. Key specifications: operating frequency 125 kHz, 16 electrodes, signal-to-noise ratio 106 dB, frame rate 120 frames/second. Image reconstruction employs a high-resolution 3D algorithm integrating fringe effect compensation and CT priors, developed by our team. These computed tomography (CT) priors were used during the algorithm development stage to optimize reconstruction performance and were not required as part of the real-time EIT monitoring procedure in this clinical study. Although the electrode array is two-dimensional at the body surface, the reconstruction algorithm estimates 3D volumetric changes within the predefined pelvic region of interest.

Reference standard

A conventional uroflowmeter will be used as the reference standard. The measurement equipment includes uroflowmeter, water cup, timer, and data recording forms. VV, flow rate, and voiding time will be recorded.

Experimental workflow (Figure 1)

Figure 1 Flowchart of the synchronized monitoring procedure comparing EIT with standard uroflowmetry. After preparation, participants underwent continuous EIT monitoring during bladder filling. Upon the urge to void, patients voided into a uroflowmeter while the EIT device simultaneously reconstructed the decreasing bladder volume in real-time. The procedure concluded with data collection, device removal, and participant feedback. BPH, benign prostatic hyperplasia; EIT, electrical impedance tomography.

• Screening and consent: eligible patients sign informed consent.
• Baseline emptying: participants attempt to empty their bladder as completely as possible.
• Device setup: the EIT electrode patch is placed on the lower abdomen over the bladder region; baseline impedance is recorded.
• Rapid water ingestion: participants drink approximately 1000 mL of pure water within 15–20 minutes.
• Filling phase monitoring: EIT continuously records impedance changes during bladder filling. Participants rest in a comfortable position (sitting or supine) until a strong desire to void is reported. To minimise variability in subjective urine‑holding, the maximum observation time is set at 45 minutes.
• Voiding phase monitoring: participants void into the uroflowmeter. Simultaneously, the EIT device dynamically reconstructs the decrease in bladder volume over time.
• Data collection and device removal: EIT data are saved; the electrode patch is removed.
• Comfort questionnaire: participants complete a questionnaire regarding wearing comfort.
• Data archiving: all data are assigned unique IDs and entered into a secure database.

Endpoints

Primary objectives

To evaluate whether the EIT intelligent wearable device can achieve clinically acceptable agreement with the reference method in determining key urinary flow parameters, including Qmax, Qave, VV and flow-curve characteristics in patients with BPH, using traditional uroflowmetry as the reference standard.

Secondary objectives

To investigate the device’s capability for real-time, dynamic, and continuous monitoring of bladder volume changes during voiding in patients with BPH, and to validate its potential to replace traditional uroflowmetry by assessing the temporal alignment precision and overall curve similarity for key flow parameters between the EIT-reconstructed data and the uroflowmetry curve.

To preliminarily develop an intelligent analysis system framework, based on dynamically acquired 3D morphological data from the EIT device and integrated with machine learning and artificial intelligence (AI) models, that can translate physiological signal data into effective clinical information, laying the technical groundwork for future home-based management and telemedicine intelligent monitoring solutions.

This study aims to comprehensively validate the overall performance of this EIT device through the achievement of the above objectives, with the goal of overcoming the numerous drawbacks of traditional uroflowmetry and providing new evidence and methods for the long-term, dynamic, non-invasive voiding monitoring management of BPH.

Sample size estimation

The sample size was calculated based on an expected intraclass correlation coefficient (ICC) of 0.85 for Qmax between EIT and uroflowmetry, assuming a null hypothesis of ICC ≤0.70 and an alternative hypothesis of ICC >0.70, with a power of 80% and a two-sided significance level of 0.05. Using the formula for one‑sample ICC testing, a minimum of 34 patients is required. Accounting for a 15% dropout rate due to invalid voiding or data loss, we aim to enroll 40 patients.

Statistical analysis

Statistical analyses will be performed using R software version 4.3.2. For paired within-subject comparisons, normally distributed variables will be analyzed using the paired t-test, whereas non-normally distributed variables will be analyzed using the Wilcoxon signed-rank test. For key paired continuous parameters, including Qmax, Qave, and VV, clinically acceptable agreement will be evaluated primarily by Bland-Altman analysis with 95% limits of agreement. The limits of agreement will be interpreted against approximate clinically meaningful ranges (e.g., around ±3 mL/s for Qmax, ±2 mL/s for Qave, and ±50 mL for VV), derived from known test–retest variability of conventional uroflowmetry and reported minimum clinically important differences. ICC will be used as a supplementary measure of consistency, interpreted against a prespecified threshold of ≥0.75, consistent with the “good reliability” benchmark proposed by Koo and Li (2016) (15). ICC will be calculated using a two-way mixed-effects, absolute-agreement model. The 95% confidence interval will be reported, and the P value will be provided for completeness only. Clinical acceptability will be determined based on the combined interpretation of Bland-Altman limits of agreement and ICC across the primary parameters, rather than on a single statistical metric. Paired hypothesis tests will be used only to characterize the direction and magnitude of systematic differences and will not serve as the primary decision criterion. Dynamic time warping (DTW) distance will be used as a descriptive secondary index of waveform temporal alignment, without a predefined pass/fail criterion. Pearson correlation will likewise be used as a supportive descriptive measure of waveform similarity and will not be used to determine clinical agreement. A P value <0.05 will be considered statistically significant where applicable.

Bias control

The accuracy of uroflowmetry depends on the bladder volume before voiding (after water ingestion and holding). Real-time dynamic EIT imaging data during the storage phase can be used to remind patients to avoid excessive bladder distension. Before trial data collection, participants can be guided to practice holding urine and perform a simulated uroflowmetry test, aiming for subjects to proficiently and accurately complete the formal uroflowmetry test.

The EIT operators/algorithm engineers and the personnel handling uroflowmetry data are blinded to each other’s results during the analysis phase. The statistical analyst is blinded to the device categories corresponding to the data groups.

Quality control

All research personnel will receive standardised training. The equipment will be calibrated regularly. Patients and family members will receive guidance on device application and the voiding test procedure to ensure data collection accuracy. Data will be collected, uploaded, and reviewed promptly.

Data management

Double data entry independently by two persons, followed by a consistency verification.

Establishment of a query form mechanism to inquire about abnormal or missing data from the investigators, with records retained.

Data review and locking: The final database will be locked after a joint review by the principal investigator, data manager, and statistician.

Safety monitoring and stopping guidelines

The procedures involved in this study are all non-invasive, and safety is controllable. Any safety events related to the trial that occur during the experimental process will be actively and promptly treated with the assistance of the project team. For elderly male participants with cardiac or renal insufficiency, it is necessary to guard against the cardiac and renal burden and other discomfort reactions caused by one-time consumption of 1000ml of water, and guide them to withdraw from the trial if necessary.

Termination of individual subject participation

The participation of a subject in the study shall be terminated immediately upon the occurrence of any of the following circumstances:

• Occurrence of a serious adverse event: any serious adverse event judged by the investigator to be related to the use of the study device or study procedures (e.g., rapid water ingestion);
• Occurrence of intolerable discomfort: the subject experiences intolerable physical discomfort or psychological stress during device wear, measurement, or after water ingestion, and actively requests withdrawal;
• Investigator’s judgment to terminate: the investigator identifies any medical condition in the subject that may increase the risk by continuing participation (e.g., symptoms of acute heart failure or renal insufficiency induced by water ingestion), or discovers that the subject does not meet the inclusion criteria;
• Subject withdrawal of informed consent: the subject may withdraw informed consent and exit the study at any time, without providing any reason.

Suspension or early termination of the entire study

The principal investigator, in coordination with the Ethics Committee, will reassess the entire study and decide whether to suspend or terminate the entire study early upon the occurrence of any of the following circumstances:

• Occurrence of major safety issues: multiple (≥3 cases) unexpected and serious adverse events possibly related to the study device or procedures occur within the study population.
• Systemic device failure: the study device is confirmed to have fundamental design defects or systemic failures, rendering it unable to collect valid and reliable data, and requiring major factory corrections.
• Inability to achieve study validity: due to poor data quality, low consistency, or other reasons, statistical evaluation indicates that the study can no longer achieve the preset primary endpoint objectives.
• Ethics committee decision: this study complies with the decisions of the Ethics Committee. If the Ethics Committee requires the study to be suspended or terminated for any reason, the study will be conducted immediately.
• Other force majeure: occurrence of force majeure events, such as public health incidents, preventing the study from proceeding as planned.

All study termination events, whether for individuals or the entire study, will be documented in detail and reported to the Ethics Committee promptly according to regulations.

Ethics and dissemination

This study was approved by the Medical Research Ethics Committee of Peking University Third Hospital (No. [2026]0111-01, approved 12 January 2026). The rights and interests of the participants will be protected, and written informed consent will be obtained from all subjects. The trial is registered with ClinicalTrials.gov (NCT07357012). Results will be disseminated through peer‑reviewed publications and conference presentations, regardless of outcome. All research data will be kept strictly confidential. The study will be conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Discussion

This study aims to evaluate the performance of an intelligent wearable device based on EIT for dynamically monitoring bladder function in patients with BPH. The anticipated results will be interpreted and contrasted with existing clinical practices from several key perspectives.

The core innovation of this study lies in exploring the ability of EIT technology to dynamically and continuously monitor the entire voiding process and reconstruct a urinary flow curve. We predict that the “volume-time” curve reconstructed by the EIT device will be highly similar to the curve obtained by the uroflowmeter, with temporal alignment errors for key event points (e.g., Qmax) at the millisecond scale. Achieving this goal would mark a significant shift in bladder voiding function monitoring from traditional “static snapshots” (single parameters from uroflowmetry) to “dynamic video”. This dynamic monitoring capability has the potential to reveal complex voiding patterns hidden behind single uroflowmetry values, providing clinicians with richer assessment dimensions. Furthermore, by analyzing the agreement stratified by different initial bladder volume states after holding, we hope to identify the optimal operating conditions for the device, guiding subsequent personalized applications.

The performance of the EIT system underpinning this study is the cornerstone for achieving the above objectives. The self-developed measurement system with a high signal-to-noise ratio (106 dB) and high-speed data acquisition (120 frames/second) provides a hardware guarantee for capturing rapid impedance changes during voiding. The high-resolution 3D reconstruction algorithm, which integrates fringe effect compensation and CT priors, is key to achieving accurate volume calculation and morphological reconstruction. Previous phantom and in vivo experiments have demonstrated that this algorithmic framework outperforms many existing algorithms regarding accuracy, providing a solid technical foundation for obtaining reliable data in this clinical study.

If the results meet expectations, the clinical implications will be profound. The non-invasive, non-ionizing during monitoring, portable, and dynamic monitoring characteristics of EIT technology position it to overcome the main drawbacks of existing uroflowmetry (16,17). It can allow assessment in a state closer to the patient’s natural condition, potentially yielding more authentic physiological data by reducing the “white coat” effect associated with clinical settings. More importantly, this study paves the way for the ultimate realization of long-term home monitoring and remote telemedicine management for BPH patients (18). By combining the continuous data stream acquired by the EIT device with machine learning/AI models, future development could yield intelligent analysis systems capable of automatically identifying abnormal voiding patterns, warning of urinary retention risks, and assisting physicians in diagnosis and treatment decisions, thereby truly revolutionizing the disease management paradigm for patients with BPH (19,20).

This study has some limitations. First, it is a single-center study with a relatively limited sample size, and the generalizability of its results requires further validation through larger-scale, multi-center studies. Second, although measures have been taken (e.g., blinding and synchronized measurements) to control bias, the performance of the EIT reconstruction algorithm might still be influenced by individual differences in abdominal tissue composition or body habitus. Additionally, the requirement for rapid water ingestion within a specific time frame may limit its applicability in some elderly patients with cardiac or renal insufficiency. Although the wearable EIT device may have the potential to estimate post-void residual volume through continuous volumetric monitoring, residual volume measurement was not a prespecified validated endpoint in the present study and was not formally assessed against an independent reference standard; this issue warrants further investigation in future studies.

Looking ahead, based on the findings of this study, subsequent work will focus on two main directions: first, continuously optimizing EIT hardware and algorithms to enhance their robustness and generalizability under complex physiological conditions; second, delving deeper into the associations between dynamic EIT data and clinical outcomes (e.g., prediction of surgical efficacy, assessment of disease progression), promoting its evolution from a functional monitoring tool to a precise diagnostic and prognostic tool.

In summary, this study will systematically validate an innovative EIT wearable technology for bladder function assessment in patients with BPH. The expected results will preliminarily demonstrate the accuracy and feasibility of this technology for the dynamic, non-invasive monitoring of bladder volume and urinary flow rate. This study represents a meaningful exploration of overcoming the limitations of current clinical monitoring methods and lays an important theoretical and practical foundation for developing the next generation of intelligent and convenient urological diagnostic tools.

Acknowledgments

The authors thank all participants in this study. We also acknowledge the technical support from our engineering team at Beihang University and the clinical staff at the Department of Urology, Peking University Third Hospital, for facilitating patient recruitment.

Footnote

Reporting Checklist: The authors have completed the SPIRIT reporting checklist. Available at https://tau.amegroups.com/article/view/10.21037/tau-2026-1-0156/rc

Peer Review File: Available at https://tau.amegroups.com/article/view/10.21037/tau-2026-1-0156/prf

Funding: This work was supported by Peking University Third Hospital “Eaglet Plan” Innovation and Transformation Fund (No. BYSYCY2025040) and Peking University Third Hospital Clinical Cohort Construction Project (No. BYSYDL2025026).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tau.amegroups.com/article/view/10.21037/tau-2026-1-0156/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study will be conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Medical Research Ethics Committee of Peking University Third Hospital (No. [2026]0111-01). Written informed consent will be obtained from all participants.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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