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Biomechanical measurement data study of human gait patterns for the development and validation of predictive simulations under orthotic-specific boundary conditions

Biomechanical measurement data study of human gait patterns for the development and validation of predictive simulations under orthotic-specific boundary conditions - BiOSim gait measurement data study

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
DRKS
Registry ID
DRKS00038763
Enrollment
20
Registered
2026-01-12
Start date
2026-07-03
Completion date
Unknown
Last updated
2026-08-03

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

Conditions

Biomechanical measurement data collection of human gait patterns for the development and validation of predictive simulations under varying modeled orthosis-specific boundary conditions.

Interventions

Group 1: The recruitment of subjects takes place both within and outside Ulm University of Applied Sciences by means of notices and direct contact with interested parties. Each participant undergoes a

Sponsors

Technische Hochschule Ulm
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 60 Years

Inclusion criteria

Inclusion criteria: Signed and dated consent form of the subject.

Exclusion criteria

Exclusion criteria: - Known allergic reaction to Kinesio tapes/adhesives - Presence of an acute general illness or orthopedic condition that prevents participation - Pregnancy

Design outcomes

Primary

MeasureTime frame
The collected measurement data will be used to create and evaluate predictive biomechanical simulations. The aim is to investigate the extent to which predictive biomechanical simulations can represent differences in gait patterns under varying modeled orthosis-specific boundary conditions. For this purpose, the defined biomechanical measurement data will be systematically collected and evaluated.

Secondary

MeasureTime frame
The secondary endpoint is the evaluation of the quality, completeness, and reproducibility of the biomechanical data set collected. This is done by means of a statistical evaluation of the measured kinematic, kinetic, and muscular variables and by analyzing the measurement variability under the defined test conditions.

Countries

Germany

Contacts

Public ContactMichael Munz

Technische Hochschule Ulm

michael.munz@thu.de+49 731 96537538

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Aug 10, 2026