Decision by majority by thinking

Abstract

This paper describes a technique for decision by majority by applying brain signal analyses. The ElectroEncephaloGram (EEG) of twenty-four volunteers were recorded with the serial presentations of Computer-Generated (CG) images of human emotional faces. We focused on the Event-Related Potential (ERP) P300 signals and the amplitude was investigated varying the ratio of collaborative P300 occurrences in the group. The supervised machine learning technique was used to perform the decision by majority and the estimation performance value could be almost 80%. This novel concept would be applicable to the decision by majority for Computer-Supported Cooperative Work (CSCW) such as Virtual Reality (VR) interactions only by means of thinking.