Search
FPGA laboratory
Department of Circuit Theory, Technická 2, 166 27 Praha 6Tel.: 224 352 288, Fax: 233 339 805
http://amber.feld.cvut.cz/fpga
Who are we?
Jakub ©»astný
His interests include digital signal processing of biological signals (mainly human EEG) and design and analysis of EEG classification algorithms. Further, he is interested in the specific problems of design of digital logic devices for digital signal processing. Head of the FPGA laboratory.
Jaromír Doleľal
His interests include real-time recognition and processing of EEG signals for the BCI devices.
Vladimír Černý
His interests include real-time recognition and processing of EEG signals for the BCI devices.
Milan Kostílek
His interests include off-line and on-line recognition and processing of EEG signals, algorithms for signal to noise ratio improvement of EEG.
Martin Dobiáą
His interests include real time as well as off-line blind source separation algorithms with the applications in the field of BCI.
Which research are we interested in?
We are dealing with pressing issues in the field of processing, analysis and recognition of biological signals; some example of our field of interests follow:
- design of blind source separation and subspace filtering algorithms for improvement of signal to noise ration of EEG signals
- high-resolution EEG signal classification
- recognition of EEG signals in real time, design of a Brain-Computer Interface
- implementation and optimization of digital logic circuits for a specialized digital signal processing tasks
What is it good for?
The results of our research will find application in the field of the Brain Computer Interface research. BCIs have been slowly penetrating the real world applications in the field of rehabilitation engineering and many other applications are envisioned (eg entertainment systems).
What we are working on, today
Brain Computer interface is a device allowing a direct communication between human brain and a computer without a need for peripheral muscles activity. The idea behind such a device is to help paralyzed patients to control the computer. However, there are other emerging applications of this concept in the fields of entertainment, biometry, and even military applications.
Our current research is targeted to the development and optimization of signal processing algorithm aimed to increase the number of types of recognized mental activities. In the end we would like to be able to recognize movements performed on the same side of body (eg right hand finger movements) using the EEG signal. This should lead in the future to increase of the information transfer rate of the communication channel between the human brain and a computer. We are dealing with the whole EEG signal processing chain (recording, filtering, artifact separaration, parametrization, and recognition).
A classifier based on Hidden Markov Models allowing high resolution movement EEG classification was developed in the frame of our research.
Nowadays we have been working on the design and development of the real time EEG processing BCI prototype and we are dealing also with other connected topics (eg utilization of the interpersonal EEG variability).
We have realized the first prototype of our BCI device, see video on the WWW pages of our laboratory.
Supporting Grants
Our work has been supported by the research program Transdisciplinary Research in Biomedical Engineering II No. MSM 684 0770012 of the Czech Technical University in Prague, and the Grant GACR 102/08/H008: Biological and Speech Signal Modelling. We are also supported by Grant Agency of the Czech Technical University in Prague, grant No. SGS10/178/OHK3/2T/13.
Cooperating institutions
The research in the field of EEG signal processing is being done in cooperation with the Charles University in Prague (Faculty of Medicine in Hradec Králové)
Selected publications
- ©»astný, J., Sovka, P.: The 3D approach to the surface Laplacian filtering with integrated sampling error compensation. Elsevier Signal Processing, pages 51 - 60. January 2007.
- ©»astný, J., Sovka, P.: High-Resolution Movement EEG Classification. Accepted 23 September 2007. To Appear in Computational Intelligence and Neuroscience, Hindawi publishing company.
- Ručkay L., ©»astný J., Sovka P.: ICA Model Order Estimation Using Clustering Method. Radioengineering, vol. 16, no. 4. Special Issue: Advanced Digital Signal Processing, pp. 51-57, 2007.
- Doleľal J., ©»astný J.: Exploiting Temporal Context in High-Resolution Movement-Related EEG Classification, to appear in Radioengineering
- ©»astný J.: FPGA prakticky, BEN Praha 2011, 200 stran