Accepted for/Published in: JMIR Research Protocols
Date Submitted: May 29, 2026
Date Accepted: Jun 26, 2026
Digital Acoustic Uroflowmetry for Non-Invasive Urine Flow Rate Monitoring on Men using Smartphone Acoustic Pattern Recognition: Protocol for a System and Mobile App
ABSTRACT
Background:
Lower urinary tract symptoms (LUTS) are a significant global health burden with severe quality of life impact. Uroflowmetry, the gold standard assessment for measuring urinary flow, may be inaccessible due to equipment availability or cost, especially in developing countries such as Indonesia. Meanwhile, the proliferation of smartphones even in developing countries offers a promising infrastructure for developing an innovative tool. Utilizing built-in microphone in smartphones to capture and analyze voiding sounds to estimate urine flow parameters has emerged as a potential solution to overcome these limitations.
Objective:
To develop a digital acoustic uroflowmetry system and a mobile application based on acoustic pattern recognition for non-invasive estimation of key urine flow parameters.
Methods:
This protocol is an observational study using cross-sectional design. A smartphone application will be developed to record voiding sounds. Customized signal processing algorithms will be designed to analyze acoustic signals and estimate urine flow parameters accordingly. Participants will be recruited from urology clinics patients, of whom each participant will undergo measurement using both conventional uroflowmetry and acoustic uroflowmetry application. The application will guide users on proper smartphone placement during voiding to ensure input quality. Acoustic features will be extracted and models will be trained and validated. The primary outcome will be the correlation and agreement between Qmax, Qavg, and VV measured by the acoustic uroflowmetry app and conventional uroflowmetry.
Results:
This study is currently at the protocol development stage. Preliminary feasibility studies are anticipated to commence in mid 2026. The full results of the development and validation study are expected by early 2027.
Conclusions:
The development of a digital acoustic uroflowmetry system using acoustic pattern recognition is designed to enhance the accessibility and convenience of urine flow monitoring, particularly for patients in regions with limited healthcare infrastructure. Clinical Trial: N/A
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