MedTrace Logo

inContAlert: Machine Learning Algorithms for Individual Bladder Filling Level Prediction

NCT05952700 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 36

Last updated 2025-04-20

No results posted yet for this study

Summary

The aim of this study is to evaluate the bladder filling level of the study participants using the inContAlert sensor. The generated data will be used for the evaluation and optimization of the machine learning algorithms to be able to make precise predictions about the individual bladder fill level.

In particular, the hypothesis that the bladder filling level can be estimated by the algorithm will be tested. When testing the hypothesis, it should be determined which deviation (measured by the mean absolute percentage error) of the estimation/prediction differs from the actual value (obtained by measuring the urine output using a measuring cup in combination with kitchen scales).

Conditions

  • Monitoring of the Bladder Filling

Interventions

DEVICE

inContAlert

InContAlert is a non-invasive sensor technology to measure the bladder filling level for incontinence patients. The device is fixed about 2cm above the pubic bone using a patch or strap and does not require surgery. The data collected from the patient is analyzed using deep learning algorithms. The bladder filling level determined in this way is then displayed on an app.

Sponsors & Collaborators

  • University of Bayreuth

    collaborator OTHER

  • inContAlert GmbH

    lead INDUSTRY

Principal Investigators

  • Jannik Lockl, Dr. · inContAlert GmbH

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-03-01
Primary Completion
2024-07-31
Completion
2024-07-31

Countries

  • Germany

Study Locations

More Related Trials

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05952700 on ClinicalTrials.gov