Objective　A　practical　and　highly　accurate　algorithm　for　dynamic　monitoring　of　plantar　pressure　was　proposed,　the　magnitude　of　vertical　ground　reaction　force　(vGRF)　during　walking　was　measured　by　a　capacitive　insole　sensor,　and　reliability　of　the　prediction　accuracy　was　verified.　Methods　Four　healthy　male　subjects　were　require　to　wear　capacitive　insole　sensors,　and　their　fast　walking　and　slow　walking　data　were　collected　by　Kistler　three-dimensional　(3D)　force　platform.　The　data　collected　by　the　capacitive　insole　sensors　were　pixelated,　and　then　the　processed　data　were　fed　into　a　residual　neural　network,　ResNet18,　to　obtain　high-precision　vGRF.　Results　Compared　with　analysis　of　the　data　collected　from　Kister　force　platform,　the　normalized　root　mean　square　error　(NRMSE)　for　fast　walking　and　slow　walking　were　8.　40%　and　6.　54%,　respectively,　and　the　Pearson　correlation　coefficient　was　larger　than　0.　96.　Conclusions　This　study　provides　a　novel　algorithm　for　dynamic　measurement　of　GRF　in　mobile　scenarios,　which　can　be　used　for　estimation　of　complete　GRF　outside　the　laboratory　without　being　constrained　by　the　number　and　location　of　force　plates.　Potential　application　areas　include　gait　analysis　and　efficient　capture　of　pathological　gaits.　©　2023　Shanghai　Jiaotong　University　School　of　Medicine.　All　rights　reserved.