Currently,　the　aging　population　in　China　is　becoming　increasingly　severe.　Research　has　shown　that　85%　of　the　elderly　have　varying　degrees　of　psychological　problems,　and　27%　of　the　elderly　have　obvious　psychological　disorders　such　as　anxiety　and　depression.　The　demand　for　offline　and　online　consultation　and　intervention　services　is　becoming　increasingly　urgent.　However,　there　is　currently　a　lack　of　systematic　mental　health　intervention　strategies　targeting　the　elderly　in　relevant　research　and　application　practices.　In　order　to　explore　new　intervention　services　such　as　online　consultation　and　chat　with　the　elderly　on　mental　health,　a　prototype　system　of　question　and　answering　for　the　elderly　mental　health　has　been　designed,　focusing　on　providing　the　elderly　and　related　caregivers　with　daily　psychological　counseling　services　for　the　elderly.　Firstly,　a　public　mental　health　Q&A　dataset　has　been　collected,　and　then　the　data　have　been　manually　screened　to　obtain　mental　health　Q&A　dataset　for　the　elderly.　Based　on　this　dataset,　combined　with　the　semantic　data　related　to　neurology　for　the　elderly,　the　knowledge　graph　of　mental　health　of　the　elderly　has　been　constructed.　Then,　the　problem　matching　module　has　been　used　to　determine　and　analyze　the　types　of　problems　faced　by　the　elderly　and　generate　corresponding　answers　to　the　questions.　For　the　questions　related　to　psychological　counseling　of　the　elderly,　the　BERT　and　BiLSTM-CRF　network　have　been　used　to　calculate　the　question　template　closest　to　the　user’s　question　in　the　system,　and　find　the　corresponding　answer　matching　the　question　in　the　knowledge　graph.　The　experimental　results　show　that　the　system　can　effectively　understand　the　intention　of　elderly　users　to　ask　questions,　and　has　good　accuracy　and　reliability　in　answering　elderly　mental　health　related　questions,　which　helps　to　address　the　mental　health　service　needs　of　the　elderly.　©　The　Author(s),　under　exclusive　license　to　Springer　Nature　Singapore　Pte　Ltd　2023.