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Authors: Hendrik Woehrle 1 ; Johannes Teiwes 2 ; Mario Michael Krell 2 ; Elsa Andrea Kirchner 3 and Frank Kirchner 3

Affiliations: 1 German Research Center for Artificial Intelligence (DFKI GmbH), Germany ; 2 University of Bremen, Germany ; 3 German Research Center for Artificial Intelligence (DFKI GmbH) and University of Bremen, Germany

ISBN: 978-989-8565-80-8

Keyword(s): Brain Computer Interface, Signal Processing, Machine Learning, FPGA, Embedded Systems, Mobile Computing.

Related Ontology Subjects/Areas/Topics: Brain-Computer Interfaces ; EEG/ERP/EOG Signal Processing ; Health Engineering and Technology Applications ; Mobile and Embedded Devices ; Neural Rehabilitation ; NeuroSensing and Diagnosis ; Neurotechnology, Electronics and Informatics

Abstract: Brain activity is more and more used for innovative applications like Brain Computer Interfaces (BCIs). However, in order to be able to use the brain activity, the related psychophysiological data has to be processed and analyzed with sophisticated signal processing and machine learning methods. Usually these methods have to be calibrated with subject-specific data before they can be used. Since future systems that implement these methods need to be portable to be applied more flexible tight constraints regarding size, power consumption and computing time have to be met. Field Programmable Gate Arrays (FPGAs) are a promising solution, which are able to meet all the constraints at the same time. Here, we present an FPGA-based mobile system for signal processing and classification. In addition to other systems, it is able to be calibrated and adapt at runtime, which makes the acquisition of training data unnecessary.

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Paper citation in several formats:
Woehrle, H.; Teiwes, J.; Krell, M.; Kirchner, E. and Kirchner, F. (2013). A Dataflow-based Mobile Brain Reading System on Chip with Supervised Online Calibration - For Usage without Acquisition of Training Data.In Proceedings of the International Congress on Neurotechnology, Electronics and Informatics - Volume 1: NEUROTECHNIX, ISBN 978-989-8565-80-8, pages 46-53. DOI: 10.5220/0004637800460053

@conference{neurotechnix13,
author={Hendrik Woehrle. and Johannes Teiwes. and Mario Michael Krell. and Elsa Andrea Kirchner. and Frank Kirchner.},
title={A Dataflow-based Mobile Brain Reading System on Chip with Supervised Online Calibration - For Usage without Acquisition of Training Data},
booktitle={Proceedings of the International Congress on Neurotechnology, Electronics and Informatics - Volume 1: NEUROTECHNIX,},
year={2013},
pages={46-53},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004637800460053},
isbn={978-989-8565-80-8},
}

TY - CONF

JO - Proceedings of the International Congress on Neurotechnology, Electronics and Informatics - Volume 1: NEUROTECHNIX,
TI - A Dataflow-based Mobile Brain Reading System on Chip with Supervised Online Calibration - For Usage without Acquisition of Training Data
SN - 978-989-8565-80-8
AU - Woehrle, H.
AU - Teiwes, J.
AU - Krell, M.
AU - Kirchner, E.
AU - Kirchner, F.
PY - 2013
SP - 46
EP - 53
DO - 10.5220/0004637800460053

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