Commercialized electroencephalography (EEG) sensors are available that one could extract EEG data more cheaply and more easily. As commercialized EEG sensors can be used commonly, the services that could be provided using EEG and interactions that can be achieved by EEG are needed to be studied. In this paper, we show the feasibility of integrating EEG based services and interactions into consumer electronics using commercialized EEG sensors. We use support vector machine (SVM) classifiers to classify the user’s status using EEG data gathered from objects of interest and noise. The results show that EEG gathered from commercialized EEG sensors can be used to classify the user’s status.