M. Lee et al. (Eds.): ICONIP 2013, Part I, LNCS 8226, pp. 427–433, 2013. © Springer-Verlag Berlin Heidelberg 2013 Phase Synchrony for Human Implicit Intent Differentiation Ukeob Park, Kalyana C. Veluvolu, and Minho Lee * School of Electronics Engineering, Kyungpook National University 1370 Sankyuk-Dong, Puk-Gu, Taegu 702-701, South Korea uepark@ee.knu.ac.kr, {veluvoluk,mholee}@gmail.com Abstract. This paper focuses on discriminating user’s intent to real images based on phase synchrony in EEG. The goal is to differentiate user's naviga- tional intention and informational intention with real world scenario’s. In this paper, we first calculate Phase locking Value (PLV) between all electrode pairs in EEG collection montage. We identified several most significant pairs (MSP) to construct brain functional connectivity patterns in different bands, theta band (4~7Hz), alpha (8~13Hz), beta-1 (14~22Hz), beta-2 (23~30Hz). Based on the PLV variation in the selected MSP’s, the user intent can be classified. This pa- per demonstrates the potential of these identified brain electrode pairs in cogni- tive detection and task classification for future BCI applications. Keywords: brain-computer interface (BCI), electroencephalographic (EEG), phase synchrony, brain connectivity, intent recognition. 1 Introduction Brain cognitive fusion technology is an emerging and most promising fusion technol- ogy floating in modern society / future of the 21st century. Especially, according to FET2012 January [1], it was written that cognitive science is one of the most impor- tant future technology. Information & Communication Technology (ICT) systems should serve as empathic cognitive extensions of their users, being active and instru- mental in driving interactions with computers as well as with other humans, hereby learning and adapting with the user. Brain plasticity and behavior is needed in order to interact between human and computer for understanding the impact on Human devel- opment [1]. According to the theory of mind [2], human beings have a natural way to represent, predict and interpret the intention expressed explicitly or implicitly by the others. For an efficient human computer interaction system it is necessary for a sys- tem to understand the intention of a human. Intention recognition is a relatively new field that is being widely used in web applications [3] and internet security [4]. Many researchers have investigated the decision discrimination in a variety of ways. In par- ticular, upon analyzing the brain science, EEG method is a non-invasive measurement of brain's electrical activity which has a good temporal resolution. Also, to understand * Corresponding author.