Author, institution: Ignas Martišius, Kauno University of Technology
Scientific Supervisor: – prof. dr. Robertas DAMAŠEVICIUS (Kaunas University of Technology, technology sciences, informatics engineering – 07T)
Science area, field: technology sciences, informatics engineering – 07T
The Doctoral Dissertation is available and at the libraries of Kaunas University of Technology (K. Donelaičio St. 20, Kaunas) and Vilnius Gediminas Technical University (Saulėtekio al. 14, Vilnius).
Dissertation Defence Board of Informatics Engineering Science Field:
prof. habil. dr. Rimvydas SIMUTIS (Kaunas University of Technology, technology sciences, informatics engineering – 07T) – chairman;
prof. dr. Aleksandr BULATOV (Lithuanian University of Health Sciences, biomedical engineering, biology – 01B);
doc. dr. Arnas KACENIAUSKAS (Vilnius Gediminas Technical University, technology sciences, informatics engineering – 07T);
doc. dr. Olga KURASOVA (Vilnius University, technology sciences, informatics engineering – 07T);
prof. dr. Bart VANRUMSTE (Catholic University of Leuven, technology sciences, informatics engineering – 07T).
Annotation:
The dissertation presents algorithms for a direct human brain – computer interface. In today’s world, more and more attention is paid to the disabled people’s quality of life, and the development of interactive entertainment and virtual reality systems. A creation of the brain – computer interface system might produce one of the most promising solutions. This interface allows a person to control a computer or other electronic device without the use of muscles. The interface is based on the transformation of the electroencephalogram brain signals to control various electronic devices.
The objective of the work is to research signal processing and classification algorithms for an electroencephalographic signal in order to create an efficient and commercially acceptable to the interface architecture.
The thesis analyzes the signal characteristics of the electroencephalographic signal, provides an overview of modern brain – computer interface system design and their classification. The research part of the dissertation describes five novel methods for signal noise reduction, feature extraction and classification. Finally, a prototype system design based on the proposed algorithms is presented, together with conclusions and practical recommendations.
