The　gesture　recognition　(GR)　technology　as　one　of　the　human-machine　interfaces　can　conveniently　and　effectively　express　the　intention　of　human　and　has　become　the　hot　research　hot　spot　in　recent　years.　Force　level　is　a　key　factor　while　GR　for　more　dexterous　and　natural　prosthetic　control.　To　provide　researchers　with　a　systematic　and　quick　overview　of　the　relevant　and　future　developments　in　GR　and　force　assessment　(FA)　techniques,　this　review　synthesizes　current　commonly　used　sensor　interfaces,　data　processing　methods,　and　methods　that　have　improved　recognition　performance.　The　experimental　design　and　related　results　of　GR　and　FA　with　various　types　of　sensors　are　analyzed　and　compared　to　understand　the　scope　of　application　and　recognition　performance　of　different　sensors.　This　review　summarizes　the　challenges　and　future　work　in　the　five　areas　of　hardware,　use　environment,　broad　applicability,　physiological　factors,　and　comfort　of　use　in　practical　applications.　Finally,　the　conclusion　prospects　that　future　research　may　need　to　focus　on　improving　model　generalization　and　robustness　to　environmental,　physiological　factors,　and　so　on　by　building　large　datasets　and　developing　flexible,　long-lasting,　lightweight,　and　senseless,　high-performance　interfaces.