Monitoring of the Bladder FillingNCT05952700
inContAlert: Machine Learning Algorithms for Individual Bladder Filling Level Prediction
An observational study of Monitoring of the Bladder Filling, run by inContAlert GmbH at 1 site in Germany.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Monitoring of the Bladder Filling
- What is being tested?
- inContAlert
- Type of treatment
- Medical device
- How many people
- 36 participants
- Where
- 1 siteGermany
- Study dates
- 1 Mar 2023to 31 Jul 2024
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: The selection of the study participants is based on a voluntary basis by inContAlert GmbH.
Who may be able to join
- informed consent
Who cannot join
- Missing informed consent
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Evaluation and Optimization of Machine Learning Algorithms for Individual Bladder Filling Level Prediction by a Sensor System
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
- Being tested
- inContAlert
- Keywords
- bladder monitoring, digital Health, bladder filling level, incontinence, neurourology, neurogenic bladder, spinal cord injury
- Medical subject headings
- Urinary Bladder, Neurogenic, Spinal Cord Injuries
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
inContAlertDevice
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.
What is being measured
The primary outcome is the main question the study is designed to answer.
Difference between the predicted bladder filling level and the actual value
Difference (measured as mean absolute error in percent) of the predicted bladder filling level (measured in ml) and the actual value (determined by measuring the volume of urine in ml with a measuring cup in combination with a kitchen scale).
Measured: December 2023
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted19 Jul 2023
- Study start1 Mar 2023
- Primary completion31 Jul 2024
- Study completion31 Jul 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Monitoring of the Bladder FillingStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case only
- Time perspective
- Prospective
- Enrolment
- 36 participants (actual)
Sponsor and investigators
- Lead sponsor
- inContAlert GmbH
- Sponsor type
- Industry (pharma, biotech, devices)
- Collaborators
- University of Bayreuth
- Responsible party
- Sponsor
- Investigators
- Jannik Lockl, Dr., Study director, inContAlert GmbH
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05952700
- Sponsor's protocol ID
- Az. O 1305/1 -GB
- Status last verified
- Apr 2025
- First submitted
- 5 Jun 2023
- Last updated
- 20 Apr 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 20 Apr 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evaluation and Optimization of Machine Learning Algorithms for Individual Bladder Filling Level Prediction by a Sensor System
- ClinicalTrials.gov ID
- NCT05952700
- Acronym / sponsor ID
- Az. O 1305/1 -GB
- Conditions
- Monitoring of the Bladder Filling
- Keywords
- bladder monitoring, digital Health, bladder filling level, incontinence, neurourology, neurogenic bladder, spinal cord injury
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 36 participants (actual)
- Lead sponsor
- inContAlert GmbHIndustry (pharma, biotech, devices)
- Collaborators
- University of Bayreuth
- Study start
- 1 Mar 2023 (actual)
- Primary completion
- 31 Jul 2024 (actual)
- Study completion
- 31 Jul 2024 (actual)
- First posted
- 19 Jul 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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).
Study design
- Observational model
- Case only
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- The selection of the study participants is based on a voluntary basis by inContAlert GmbH.
Key inclusion criteria (1 listed)
- informed consent
Key exclusion criteria (1 listed)
- Missing informed consent
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| inContAlertInContAlert 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. | Device | – |
Primary outcome
Difference between the predicted bladder filling level and the actual value
Time frame: December 2023
Difference (measured as mean absolute error in percent) of the predicted bladder filling level (measured in ml) and the actual value (determined by measuring the volume of urine in ml with a measuring cup in combination with a kitchen scale).
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 20 Apr 2025.
- Individual participant dataSharing planned: No
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Jannik Lockl, Dr. study director
inContAlert GmbH
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Monitoring of the Bladder Filling, run by inContAlert GmbH at 1 site in Germany.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 20 Apr 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Germany. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Difference between the predicted bladder filling level and the actual value (time frame: December 2023). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 20 Apr 2025.