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, (ICBET-2013), 19.5.-20.5.2013, Kopenhagen, Elsevier, 2013.
Abstract
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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.
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131018_A_Framework_for_High_Performance_Embedded_Signal_Processing_and_Classification_of_Psychophysiological_Data_ICBET_Woehrle.pdf