Trial coordinators preparing subjects for recording Motion Capture data
Trial Coordination
Depending on the study design, we recruit participants through the Tübingen Experiments Database, send recruitment e-mails to the campus or different institutions, distribute flyers and posters, or contact specific people with the right set of skills or features (actors, musicians, yoga instructors, people from a specific age group or fitness level, etc.).
Trial Coordinators schedule the experiments, carefully explain details about the study and how the data is going to be stored and used. Participants sign a consent form that specifies how their data may be used. For each session, we store this information about how the data may be published or shared. Depending on the protocol, the data capture may involve taking body measurements, putting on motion capture markers, applying make-up, or preparing clothing.
Participants receive 8 EUR – 12 EUR for taking part in the trials. The trial coordinators handle this payment.
Data Safety and Ethics
The Data Team is responsible for preparing and submitting proposals to the University of Tübingen Ethics Board and the Max Planck Society Ethics Committee and for adapting study protocols to the feedback we receive form the boards.
Data safety and our participants’ privacy are of great importance to us. We collect, store, process and share data in accordance with German national laws, European Union guidelines and the rules and standards of the Max Planck Society. In addition, we have internal procedures and measures to maintain awareness of the data privacy and data handling. We have developed a data-safety training course for department members that focuses on general rules as well as specific good practices for every step of the workflow with human subject data.
Data Management and Processing
Data Team members are responsible for the first processing steps after data is captured. Organizing the file system and securing raw data are key steps in this process.
Providing clean Motion Capture data (without inconsistencies in marker labelling) is one of the most challenging processing tasks. While multiple team members are trained to do this manually, we are moving towards using an in-house software solution to automate and speed up the process.
Perceptual Experiments and Labeling Data
The data team designs and conducts perceptual studies on Amazon Mechanical Turk. This allows us to validate results, label data, and determine its quality. To do so, we adapt HTML templates, design new labeling tasks, or adapt existing labelling solutions to the platform.