Classification of unconscious like/dislike decisions: First results towards a novel application for BCI technology

摘要

More and more applications for BCI technology emerge that are not restricted to communication or control, like gaming, rehabilitation, Neuro-IS research, neuro-economics or security. In this context a so called passive BCI, a system that derives its outputs from arbitrary brain activity for enriching a human-machine interaction with implicit information on the actual user state will be used. Concretely EEG-based BCI technology enables the use of signals related to attention, intentions and mental state, without relying on indirect measures based on overt behavior or other physiological signals which is an important point e.g. in Neuromarketing research. The scope of this pilot EEG-study was to detect like/dislike decisions on car stimuli just by means of ERP analysis. Concretely to define user preferences concerning different car designs by implementing an offline BCI based on shrinkage LDA classification. Although classification failed in the majority of participants the elicited early (sub) conscious ERP components reflect user preferences for cars. In a broader sense this study should pave the way towards a “product design BCI” suitable for neuromarketing research.