A　method　is　proposed　to　calculate　and　analyze　electro-encephalogram　signal　to　improve　the　situation　that　there　is　an　urgent　need　for　an　effective　quantitative　indicator　to　describe　brain　mental　disorders.　The　method　defines　a　spectral　entropy　in　terms　of　the　power　spectrum　division　of　time　series.　Then,　the　entropy　is　applied　to　numerical　calculation　of　electroencephalogram　signals　of　depression　patients　and　normal　control　group.　Meanwhile,　the　differences　are　compared　between　them.　Experimental　results　show　that　the　power　spectral　entropy　in　depression　patients　is　significantly　weaker　than　the　normal　healthy　people＇s　in　some　brain　regions.　Further　analysis　proves　two　facts.　One　is　that　the　entropy　is　positively　correlated　to　brain　electrical　physiological　activity,　and　the　other　tells　that　the　entropy　can　be　used　as　a　parameter　to　measure　brain　electrical　activity,　to　characterize　brain　electrical　physiological　activities,　and　to　provide　the　activity　intensity　information.　This　paper　determines　that　the　power　spectral　entropy　for　electroencephalogram　plays　an　important　role　in　diagnosis　of　brain　mental　disorder.