An important issue in electroencephalography (EEG) experiments is to measure accurately the three dimensional (3D) positions of the electrodes. We propose a system where these positions are automatically estimated from several images using computer vision techniques. Yet, only a set of undifferentiated points are recovered this way and remains the problem of labeling them, i.e. of finding which electrode corresponds to each point. This paper proposes a fast and robust solution to this latter problem based on combinatorial optimization. We design a specific energy that we minimize with a modified version of the Loopy Belief Propagation algorithm. Experiments on real data show that, with our method, a manual labeling of two or three electrodes only is sufficient to get the complete labeling of a 64 electrodes cap in less than 10 seconds. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Péchaud, M., Keriven, R., Papadopoulo, T., & Badier, J. M. (2007). Combinatorial optimization for electrode labeling of EEG caps. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4792 LNCS, pp. 793–800). Springer Verlag. https://doi.org/10.1007/978-3-540-75759-7_96
Mendeley helps you to discover research relevant for your work.