inContAlert: Designing bladder level monitoring system for neurogenic bladder patients using machine learning

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

DRKS

Registry ID

DRKS00026995

Enrollment

Registered

2022-03-02

Start date

2021-09-29

Completion date

Unknown

Last updated

2025-04-07

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Urinary incontinence and similar bladder dysfunctions R32 N39.3 N39.4 F98.0 N31 N32.8 G95.8

Interventions

Group 1: The aim of this study is to develop a wearable system for continuous bladder level monitoring for patients with neurogenic bladder dysfunction and to design a respective software architecture

Eligibility

Sex/Gender

All

Age

18 Years to No maximum

Inclusion criteria

Inclusion criteria: physician or patient with bladder dysfunction, age of majority

Exclusion criteria

Exclusion criteria: no physician or no bladder dysfunction, age of minority

Design outcomes

Primary

Measure	Time frame
Completed development of a wearable system to continuously monitor the bladder level of neurogenic bladder patients and design of a respective software architecture. Positive evaluation through interviews	—

Secondary

Measure	Time frame
Derivation of design principles for the design of systems to continuously monitor physiological parameters in chronic disease management.	—

Countries

Germany

Contacts

Public ContactRobin Weidlich

Universität Bayreuth, Projektgruppe Wirtschaftsinformatik des Fraunhofer FIT, Kernkompetenzzentrum FIM

robin.weidlich@fim-rc.de01768433888+49

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Feb 4, 2026