Matthias Honal, Tanja Schultz



Our society demands ubiquitous mobile devices that offer seamless interaction with everybody, everything, everywhere, at any given time. However, the effectiveness of these devices is limited due to their lack of situational awareness and sense for the users’ needs. To overcome this problem we develop intelligent transparent human-centered systems that sense, analyze, and interpret the user’s needs. We implemented learning approaches that derive the current task demand from the user’s brain activity by measuring the electroencephalogram. Using Support Vector Machines we can discriminate high versus low task demand with an accuracy of 92.2% in session dependent experiments, 87.1% in session independent experiments, and 80.0% in subject independent experiments. To make brain activity measurements less cumbersome, we built a comfortable headband with which we achieve 69% classification accuracy on the same task.


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Paper Citation

in Harvard Style

Honal M. and Schultz T. (2008). DETERMINE TASK DEMAND FROM BRAIN ACTIVITY . In Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2008) ISBN 978-989-8111-18-0, pages 100-107. DOI: 10.5220/0001069001000107

in Bibtex Style

author={Matthias Honal and Tanja Schultz},
booktitle={Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2008)},

in EndNote Style

JO - Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2008)
SN - 978-989-8111-18-0
AU - Honal M.
AU - Schultz T.
PY - 2008
SP - 100
EP - 107
DO - 10.5220/0001069001000107