Research on Processing the Brain Activity in BCI System

Research on Processing the Brain Activity in BCI System

Jaromir Svejda (Tomas Bata University in Zlin, Czech Republic), Roman Zak (Tomas Bata University in Zlin, Czech Republic), Roman Senkerik (Tomas Bata University in Zlin, Czech Republic) and Roman Jasek (Tomas Bata University in Zlin, Czech Republic)
Copyright: © 2017 |Pages: 27
DOI: 10.4018/978-1-5225-0565-5.ch007
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Abstract

The basic idea of BCI (Brain Computer Interface) is to connect brain waves with an output device through some interface. Human brain activity can be measured by many technologies. In our research, we use EEG (Electroencephalography) technology. This chapter will deal with processing of EEG signal and its utilization in practical applications using BCI technology mentioned above. This chapter is organized as follows. Firstly, the basic knowledge about EEG technology, brain and biometry is briefly summarized. Secondly, research of authors is presented. Finally, the future research direction is mentioned.
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Introduction

Linking the central nervous system with artificially created system is the main focus of authors’ current research. Scientific research of this field began in 1970. First experimental implants, which were intended for people, appeared after years of experiments on animals in 1990. The original idea was designing appropriate compensations for damaged senses such as hearing, sight and movement; nowadays, scientific discipline called neuroprosthetics deals with this idea. With the recent progress in technologies, it was found that it is possible to assemble system without the necessity of direct connection with central nervous system. Electrical activity of neurons may be sensed by non-invasive method, which uses special electrodes. Pioneering researches show that real applications bring rather expansion of human funcionality than just its restoration.

Many laboratories and scientific teams around the world began to develop techniques, which deals with system control through the brain activity. This kind of technology is called BCI (Brain – Computer Interface) system and it is known as the interface between computer and the brain. (Pfurtscheller, 2000) One of the first comprehensively documented system based on BCI technology was BCI2000 platform. (Schalk, 2004)

Technology itself falls into several scientific disciplines. Firstly, there are several methods, which allow measurement of brain activity (ECoG, EEG, fMRI and BOL). It is obvious that most of knowledgement about human brain are based on medicine findings. Futher, signals or data have specific form; thus, it requires the utilization of methods from signal processing, physics and mathematics. Sample recognition should be processed by some artificial neural network. (Hazrati, 2010; Kaper, 2003; Lotte, 2007) Another key issue, which should not be neglected, is communication channel selection. It is important to use such communication channel, which is effective for data transfer. Last scientific discipline, which BCI technology uses, is algorithmisation. It can be use either for software or hardware part of the system.

The aim of whole BCI is the research on creation of new communication system, which translates human initiative into signals used to control external device. Many experts present states of signal processing and classification methods in (Blankertz et al, 2004). There are quite a few solvers in this specific field of study.

Brain activity is measured through BCI system. Further, specific properties of obtained signal are derived and transferred to signals, which are appropriate to control end device. Good example is Emotiv Corporation, which developed BCI interface for interaction between human brain and computer based on processing electromagnetic waves (EEG) from the human brain. (Emotiv, 2015)

Generally, interface offers wide range of possible branches in which BCI can be used; for example, in commercial sphere: interactive applications, intelligent adaptive environment, audio-visual art and design or automotive industry. Further usage is in medicine, robotics and last but not least usage is in scientific research. (Emotiv, 2015; Esfahani, 2011; Fabiani, 2004; Gao, 2003; Guger, 2003; Lal, 2004; Li, 2009; Del Pozo-Banos, 2014; Wolpaw, 2003)

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