In medical literatures, it has been reported that the increased REM (rapid eye movement) density is one of the characters of depressed sleep. Some experiments were conducted to confirm that REM sleep deprivation (REM-SD) for a period of time is therapeutic for endogenous depressed patients. However, because of its high complexity and intensive labor requirement, this therapy has not yet been proved validity by a sufficient amount of depressed patients. Therefore, we propose to develop an automated sleep staging system using only single EEG channel to achieve on-line detection for REM state during sleep. For classifier design, we use a dataset of 25 subjects and the staging accuracy can achieve 80%. Once the REM state is detected by the system, the system will alarm the subject to deprive the REM sleep. The effect of REM sleep deprivation can be examined by hypnogram and the proposed system will be applied for clinical trials of depression therapy.