Das IISM sucht motivierte studentische Mitarbeiter (Hiwis) für die Unterstützung bei der Entwicklung einer Experimentalplattform (Java)
NeuroIS research necessitates the collection of high quality empirical data. In particular, research in this domain necessitates the collection of psychophysiological data synchronized to a subject’s current context. In order to work with a controlled environment, many researchers use lab experiments to conduct their studies and collect the above described data.
Software used in these lab experiments, either third-party or customized, often suffers from a number of limitations . Following a design science methodology, we define the objectives of an experimental platform that could be used for conducting market experiments, and integrating physiological information (such as Heart Rate, Skin Conductance Response, etc.). Currently, our platform (BROWNIE) enables logging of sensor data from each client, synchronized with the events in an experiment.
The next step is to incorporate physiological information would be to
implement real-time biofeedback  that can be presented to the
Towards this end, we are looking for a student assistant to enhance one or more of the following aspects of the platform:
- Integrate open source real-time processing algorithms (e.g., QRS-detection algorithm)
- Develop a user friendly and efficient UI for the experiment’s operator
- Implement building blocks for economic experiments
Working hours and duration of assistance are flexible and can be fixed by means of a personal interview. You will stand to gain hands-on-experience in software design, engineering, and research in experimental economics. Programming skills in Java are required, which surpass “Introduction to Programming with Java” (“Programmieren I: Java”).Supervisors: Marius Müller, Anuja Hariharan.
- Mueller, M.; Hariharan, A.; Adam, M. 2014 A NeuroIS Platform for Lab Experiments. in: Davis, F.; Riedl, R.; vom Brocke, J.; Leger, P.-M.; Randolph, A. (eds.), Gmunden Retreat on NeuroIS 2014 Proceedings. (Gmunden, Austria).
- Kristina Schaaff, Lars Müller, Malte Kirst, Stephan Heuer: xAffect - A Modular Framework for Online Affect Recognition and Biofeedback Applications. Presentation at 7th European Conference on Technology Enhanced Learning (ECTEL 2012), MATEL Workshop, Saarbrücken, Germany, 18-21 September 2012.