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Validation of an algorithm for sound-based voided volume estimation.

Gyoohwan Jung1, Hoyoung Ryu2, Jeong Woo Lee3

  • 1Department of Urology, Hanyang University College of Medicine, 222, Wangsimni-ro, Seongdong-gu, Seoul, Korea.

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A new sound-based algorithm accurately estimates urination volume, offering a convenient and precise alternative to traditional voiding diaries. This validated method supports improved urinary tract health monitoring.

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Area of Science:

  • Biomedical Engineering
  • Urology
  • Acoustic Signal Processing

Background:

  • Traditional voiding diaries for urinary tract health monitoring suffer from manual recording inaccuracies and inconvenience.
  • Sound-based voided volume estimation algorithms offer a potential solution to these limitations.

Purpose of the Study:

  • To validate a sound-based voided volume estimation algorithm (proudP) using bodyweight change as a reference.
  • To assess the algorithm's performance across a large, multi-site population.

Main Methods:

  • Collected 584 data points from 508 subjects in the US and Korea, matching urination sound data with bodyweight change after urination.
  • Employed fivefold cross-validation to evaluate the algorithm's accuracy.
  • Utilized Pearson's correlation coefficient, paired t-tests, and Bland-Altman plots for statistical analysis.

Main Results:

  • The algorithm's estimated mean voided volume was 202.6 mL (SD: ±114.8), closely aligning with the mean bodyweight change of 208.0 g (SD: ±121.5).
  • A strong linear correlation (Pearson's r = 0.92, p < 0.001) was observed between estimated and measured volumes.
  • Paired t-tests indicated equivalence within a 10 mL margin, with a Bland-Altman analysis showing a mean difference of -5.5 mL.

Conclusions:

  • The sound-based voided volume estimation algorithm demonstrates high performance and accuracy.
  • The validated algorithm offers a convenient and reliable tool for monitoring urinary tract health.
  • Results support the algorithm's applicability across diverse populations in multi-site clinical trials.