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Dr. Regine Kleber and

María García

infoZrm9∂heika-research de

Combining Statistical and Computational Modeling Approaches for User State Prediction

Combining Statistical and Computational Modeling Approaches for User State Prediction
Contact:

Prof. Dr. Joachim Funke, contact
Institute of Psychology, Heidelberg University

Prof. Dr. Tanja Schultz, contact
Institute for Anthropomatics, KIT

Project Group:

Nature, Technology, Society

Partner:Further information to the project partners from KIT and Heidelberg University:
Daniel Holt, contact
Felix Putze, contact

 

 

Startdate:

01.01.2013    

Enddate:

31.12.2013

Abstract / Summary

The aim of this HEiKA collaboration was the development of a cognitive user model of a complex learning task as basis for assistive computer technology. The user model brings together expertise from both cognitive psychology and human-centered computer science by combining two modeling approaches:
A psychologically well-founded computational model generates a-priori predictions of user states based on the simulation of cognitive processes. This prediction is combined with real-time statistical EEG-based analysis of the user’s brain activity to detect neural markers for certain internal states to yield a more accurate overall prediction.

During the project, we developed a prototype system that models learning performance in a complex reinforcement learning task using a Q-learning algorithm augmented by spectral analysis of concurrently recorded EEG.