A Framework for High Performance Embedded Signal Processing and Classification of Psychophysiological Data

Hendrik Wöhrle, Johannes Teiwes, Elsa Andrea Kirchner, Frank Kirchner

In: APCBEE Procedia. International Conference on Biomedical Engineering and Technology (ICBET-2013) 3rd May 19-20 Kopenhagen Denmark Elsevier 2013.


We present a framework to perform and speed up signal processing and machine learning tasks of biomedical and psychophysiological data in mobile and wearable systems using field programmable gate arrays. We show the basic architecture and capabilities of the framework and demonstrate its usage to construct a mobile system for the detection of event related potentials in electroencephalographic data. The performance of the developed system is evaluated in a specific application: the single trial classification of the P300 in an operator surveillance setup.


131018_A_Framework_for_High_Performance_Embedded_Signal_Processing_and_Classification_of_Psychophysiological_Data_ICBET_Woehrle.pdf (pdf, 775 KB )

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence