Comparing　with　the　traditional　way　for　hand　rehabilitation,　such　as　simple　trainers　and　artificial　rigid　auxiliary,　this　paper　presents　an　isometric　and　isotonic　soft　hand　for　rehabilitation　supported　by　the　soft　robots　theory　which　aims　to　satisfy　the　more　comprehensive　rehabilitation　requirements.　Salient　features　of　the　device　are　the　ability　to　achieve　higher　and　controllable　stiffness　for　both　isometric　and　isotonic　contraction.　Then　we　analyze　the　active　control　for　isometric　and　isotonic　movement　through　electroencephalograph　(EEG)　signal.　This　paper　focuses　on　three　issues.　The　first　is　using　silicon　rubber　to　build　a　soft　finger　which　can　continuously　stretch　and　bend　to　fit　the　basic　action　of　the　fingers.　The　second　is　changing　stiffness　of　the　finger　through　the　coordination　between　variable　stiffness　cavity　and　actuating　cavity.　The　last　is　to　classify　different　EEG　states　based　on　isometric　and　isotonic　contraction　using　common　spatial　pattern　feature　extraction　(CSP)　methods　and　support　vector　machine　classification　methods　(SVM).　On　this　basis,　an　EEG-based　manipulator　control　system　was　set　up.