International Journal of Human-Computer Studies
ACM Transactions on Computer-Human Interaction (TOCHI)
Classification of primitive shapes using brain-computer interfaces
Computer-Aided Design
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Understanding of user needs and preferences, and incorporating them into product designs are crucial for new products to be successful in today's highly competitive marketplace. This paper introduces a unique methodology to capture user preferences from biological signals. The proposed method successfully utilizes one of the most complex phenomenons of the human body, bio-signals for preference extraction. Bio-signals are magnetic fields that are generated by the neurons as a response to a person's surroundings. Due to its complexity, interpretation of bio-signals in the form of natural communication channels is extremely difficult. On the other hand, our experiments with potential users of various types of products revealed that detectable shifts from steady state levels of brain signals in the positive or negative direction are strongly correlated with the individual's preferences on alternative designs. From experiments conducted on 14 different subjects we conclude that when the alpha-peak frequencies EEG signals at the 8--12 Hz band are captured during a user's interaction with two competing product design solutions, the lower alpha-peak value indicates a higher preference over the competing product for right-sided subjects. The opposite effect is observed for the left-sided subjects.