Existing　residual　current　protectors　mostly　use　the　effective　value　of　the　total　residual　current　as　the　operating　criterion.　The　threshold　is　fixed,　and　cannot　identify　the　type　of　electric　shock.　A　low-voltage　distribution　network　living　body　electric　shock　identification　method　based　on　adaptive　threshold　and　BP　neural　network　is　proposed.　The　total　residual　current　signal　is　processed　by　Mallat　algorithm　to　reduce　noise,　and　an　adaptive　threshold　is　constructed　from　the　obtained　low-frequency　components,　which　is　used　to　determine　the　time　of　electric　shock,　extract　statistical　features　that　can　characterize　the　characteristics　of　living　bodies　and　the　BP　neural　network　is　trained　to　establish　an　electric　shock　type　recognition　model.　The　physical　simulation　results　show　that　the　method　can　meet　the　requirements　of　rapidity　and　reliability　of　the　residual　current　protector,　and　the　accuracy　rate　of　electric　shock　type　identification　is　99.93%,　which　has　reference　value　for　the　development　of　a　new　generation　of　residual　current　protection　device.　©　2022,　Power　System　Technology　Press.　All　right　reserved.