Big Data in Electroencephalography Analysis

Abstract

Human beings have broad inclinations and logical reasoning capabilities. Some of them are developed genetically, whereas some are modelled through experience. These changes can be observed in different scales and dynamics of neurons. Therefore, it is very essential to analyse the neuronal behaviour in huge data sizes over different human communities. Big data analytics is emerging rapidly as a research area. It acts as a tool to accumulate, analyse, and manage large quantity of dissimilar, structured and unstructured data, particularly in the present medical systems. Big data concept is vastly applied in the disease detection area like epileptic seizure detection. But the adaption rate and research opportunities are delayed by some basic problems in the big data model. The main objective of this chapter is to mathematically model the data generated by an Electroencephalography (EEG) recording system. It is intended to explore the use of big data in managing a huge amount of data. Application of big data in epileptic EEG analysis is also explored.