Indexing intelligence using benchmark classifier

Abstract

Human being as a parameter for assessment is a complex component for any researcher, since the field of medical sciences opens up too many unsolved queries. In this context if emotions are to be quantified it involves both scientific and certain Non-scientific issues. In terms of medical concept Electroencephalogram (EEG) helps in understanding specific regions of the brain. Since functional capabilities of regions of the brain can be understood by the probes attached to that particular region which intern provides the electrical responses. In the present work, It has been tried to encapsulate the signals in EEG to create an Index of quantification to understand the basic feelings of emotion of an Individual. As a researcher perspective to deduce any mathematical equation, a benchmark data is a major requirement. Hence to enumerate the algorithm, a specific classification model using k-NN has been taken up which enables to understand the similarity and dissimilarity factor of the recorded signals of an individual with the benchmark data.