Prof. Ronald Tetzlaff Profile

Prof. Ronald Tetzlaff

at TU Dresden

SPIE Involvement:

Author

Proceedings Article | 3 May 2011 Paper

A new cellular nonlinear network emulation on FPGA for EEG signal processing in epilepsy

Jens Müller, Jan Müller, Ronald Tetzlaff

Proceedings Volume 8068, 80680M (2011) https://doi.org/10.1117/12.886766

KEYWORDS: Electroencephalography, Signal processing, Nonlinear optics, Field programmable gate arrays, Epilepsy, Network architectures, Biomedical optics, Nanotechnology, Current controlled current source, Very large scale integration

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Proceedings Article | 3 May 2011 Paper

Spatio-temporal coupling of EEG signals in epilepsy

Vanessa Senger, Jens Müller, Ronald Tetzlaff

Proceedings Volume 8068, 80680L (2011) https://doi.org/10.1117/12.886746

KEYWORDS: Electroencephalography, Epilepsy, Electrodes, Brain, Image processing, Signal detection, Reliability, Dynamical systems, Parallel computing, Sensors

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Proceedings Article | 20 May 2009 Paper

Spatio-temporal analysis of brain electrical activity in epilepsy based on cellular nonlinear networks

Frank Gollas, Ronald Tetzlaff

Proceedings Volume 7365, 73650E (2009) https://doi.org/10.1117/12.821507

KEYWORDS: Brain, Epilepsy, Electroencephalography, Statistical analysis, Signal detection, Current controlled current source, Chromium, Nervous system, Time series analysis, Reliability

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Epilepsy is the most common chronic disorder of the nervous system. Generally, epileptic seizures appear without foregoing sign or warning. The problem of detecting a possible pre-seizure state in epilepsy from EEG signals has been addressed by many authors over the past decades. Different approaches of time series analysis of brain electrical activity already are providing valuable insights into the underlying complex dynamics. But the main goal the identification of an impending epileptic seizure with a sufficient specificity and reliability, has not been achieved up to now. An algorithm for a reliable, automated prediction of epileptic seizures would enable the realization of implantable seizure warning devices, which could provide valuable information to the patient and time/event specific drug delivery or possibly a direct electrical nerve stimulation. Cellular Nonlinear Networks (CNN) are promising candidates for future seizure warning devices. CNN are characterized by local couplings of comparatively simple dynamical systems. With this property these networks are well suited to be realized as highly parallel, analog computer chips. Today available CNN hardware realizations exhibit a processing speed in the range of TeraOps combined with low power consumption. In this contribution new algorithms based on the spatio-temporal dynamics of CNN are considered in order to analyze intracranial EEG signals and thus taking into account mutual dependencies between neighboring regions of the brain. In an identification procedure Reaction-Diffusion CNN (RD-CNN) are determined for short segments of brain electrical activity, by means of a supervised parameter optimization. RD-CNN are deduced from Reaction-Diffusion Systems, which usually are applied to investigate complex phenomena like nonlinear wave propagation or pattern formation. The Local Activity Theory provides a necessary condition for emergent behavior in RD-CNN. In comparison linear spatio-temporal autoregressive filter models are considered, for a prediction of EEG signal values. Thus Signal features values for successive, short, quasi stationary segments of brain electrical activity can be obtained, with the objective of detecting distinct changes prior to impending epileptic seizures. Furthermore long term recordings gained during presurgical diagnostics in temporal lobe epilepsy are analyzed and the predictive performance of the extracted features is evaluated statistically. Therefore a Receiver Operating Characteristic analysis is considered, assessing the distinguishability between distributions of supposed preictal and interictal periods.

Proceedings Article | 22 May 2007 Paper

Seizure prediction by delay-type single-layer discrete-time cellular nonlinear networks (DTCNN)?

Christian Niederhöfer, Frank Gollas, Ronald Tetzlaff

Proceedings Volume 6592, 659202 (2007) https://doi.org/10.1117/12.721911

KEYWORDS: Electrodes, Feature extraction, Epilepsy, Error analysis, Detection and tracking algorithms, Electroencephalography, Databases, Brain, Applied physics, Network security

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Proceedings Article | 29 June 2005 Paper

Recent results for obstacle detection by Cellular Neural Networks (CNN)

G. Geis, D. Feiden, R. Tetzlaff

Proceedings Volume 5839, (2005) https://doi.org/10.1117/12.608591

KEYWORDS: Video, Detection and tracking algorithms, Neural networks, Cameras, Video processing, Feature extraction, Edge detection, Image processing, Image enhancement, Algorithm development

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Proceedings Article | 29 June 2005 Paper

Wavelet based analysis of multi-electrode EEG-signals in epilepsy

Daniel Hein, Ronald Tetzlaff

Proceedings Volume 5839, (2005) https://doi.org/10.1117/12.608649

KEYWORDS: Wavelets, Electrodes, Epilepsy, Electroencephalography, Brain, Signal detection, Applied physics, Detection and tracking algorithms, Complex systems, Dynamical systems

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Proceedings Article | 29 June 2005 Paper

Prediction of epileptic seizures using multi-layer delay-type discrete time cellular nonlinear networks (DTCNN): long-term studies

Christian Niederhofer, Ronald Tetzlaff

Proceedings Volume 5839, (2005) https://doi.org/10.1117/12.608629

KEYWORDS: Electrodes, Brain, Electroencephalography, Epilepsy, Digital recording, Signal detection, Optimization (mathematics), Optical spheres, Neural networks, Algorithm development

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Proceedings Article | 29 June 2005 Paper

Modeling brain electrical activity in epilepsy by reaction-diffusion cellular neural networks

F. Gollas, R. Tetzlaff

Proceedings Volume 5839, (2005) https://doi.org/10.1117/12.608643

KEYWORDS: Systems modeling, Brain, Electroencephalography, Complex systems, Epilepsy, Neural networks, Electrodes, Optimization (mathematics), Diffusion, Process modeling

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Proceedings Article | 29 June 2005 Open Access

Intelligent implantable medical devices: the epilepsy problem

Ronald Tetzlaff, Christian Niederhofer, Philipp Fischer

Proceedings Volume 5839, (2005) https://doi.org/10.1117/12.609226

KEYWORDS: Electroencephalography, Electrodes, Signal detection, Detection and tracking algorithms, Epilepsy, Brain, Plasma display panels, Feature extraction, Image segmentation, Nonlinear optics

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Proceedings Article | 29 June 2005 Paper

System identification by Cellular Neural Networks (CNN): linear interpolation of nonlinear weight functions

Michael Reinisch, Gunter Geis, Ronald Tetzlaff

Proceedings Volume 5839, (2005) https://doi.org/10.1117/12.608590

KEYWORDS: System identification, Neural networks, Partial differential equations, Electronic components, Wave propagation, Wavefronts, Applied physics, Complex systems, Solitons, Chemical elements

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Proceedings Article | 21 April 2003 Paper

On-chip training for cellular neural networks using iterative annealing

Dirk Feiden, Ronald Tetzlaff

Proceedings Volume 5117, (2003) https://doi.org/10.1117/12.498954

KEYWORDS: Annealing, Image processing, Neural networks, Binary data, Computing systems, Analog electronics, Motion estimation, Statistical methods, Applied physics, Dynamical systems

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Proceedings Article | 18 April 2003 Paper

Pattern detection by CNN in epilepsy: recent results

Christian Niederhofer, Philipp Fischer, Ronald Tetzlaff

Proceedings Volume 5119, (2003) https://doi.org/10.1117/12.499916

KEYWORDS: Brain, Detection and tracking algorithms, Binary data, Epilepsy, Feature extraction, Computer simulations, Nonlinear optics, Signal processing, Complex systems, Electrodes

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Showing 5 of 12 publications

Conference Committee Involvement (5)

Bioelectronics, Biomedical, and Bio-inspired Systems

19 April 2011 | Prague, Czech Republic

Bioengineered and Bioinspired Systems

4 May 2009 | Dresden, Germany

Bioengineered and Bioinspired Systems

2 May 2007 | Maspalomas, Gran Canaria, Spain

Bioengineered and Bioinspired Systems II

9 May 2005 | Sevilla, Spain

Bioengineered and Bioinspired Systems

19 May 2003 | Maspalomas, Gran Canaria, Canary Islands, Spain

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