This paper describes a technique for human sensibility evaluation using EEGs of 4 emotions. The proposed method uses the linear predictor coefficients as EEG feature parameters and a neural network as sensibility pattern classifier. For subject independent system, multiple templates are stored and the most similar template can be selected. EEG signals corresponding to 4 emotions such as relaxation, joy, sadness and anger are collected from 5 armature performers. The states of relaxation and joy are considered as positive sensibility and those of sadness and anger as negative. The classification performance suing the proposed method is about 72.6%. This may be promising performance in the human sensibility evaluation.