| ABSTRACT |
Neuromarketing is a relatively recent area of study which combines the area of cognitive neuroscience and information technologies for marketing the product. Neuromarketing is based on the use of neuroscience to facilitate, improve and increase the results of market study techniques. Neuromarketing makes it possible to evaluate the sensory-motor, cognitive and emotional responses of a study group to a given stimulus. A novel and miniature Neuromarketing system is developed for estimating the consumers' emotional response of the product advertisement. In this work, we mainly considered five different emotions such as happy, sad, fear, anger, and surprise for emotion assessment. Several product advertisements (audio-visual stimuli) are shown to the subjects and EEG signals are acquired using 64 channel electrodes placed over the entire scalp using International 10-10 standard with a sampling frequency of 256 Hz. Acquired signals are processed using efficient signal processing algorithm and machine learning techniques are used to detect the consumers' emotional states on particular stimulus. In order to simply the computational complexity and to reduce the physical burden to the subject, we have developed our own channel selection algorithm to reduce the number of EEG channels from 64 to 8 channels by without reducing the accuracy of the system.
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