Automatic detection of open and closed eye states in electroencephalographic (EEG) records was investigated in this study as a part of procedures for the precise interpretation of the background EEG to achieve a comprehensive automatic EEG interpretation system. The features of eye open and closure were extracted from the EEG using a Markov process amplitude (MPA) EEG model, which could efficiently express the features of the EEG using a small number of parameters. A new technique, named the trigger method, was also developed to overcome the difficulty resulting from large differences in the EEG features among different subjects, because an accurate detection could not be obtained by using the conventional threshold method. The proposed method gave satisfactory results which conformed with those of visual inspection by a qualified EEGer and could be clinically used as a preprocessing method for the automatic interpretation of the awake background EEG.