The　gait　characteristics　of　an　actor　can　be　recorded　accurately　on　the　plantar　pressure　map　in　a　movement.　It　can　be　used　to　distinguish　whether　the　gait　of　this　actor　in　a　movement　is　abnormal　or　not.　Using　a　set　of　pressure　sensors,　the　plantar　pressure　during　dynamic　motion　is　collected,　and　the　kinetic　and　dynamic　characteristics　of　gait　are　extracted.　Then　extreme　learning　machines　(ELM)　neural　network　cluster　algorithm　is　used　to　the　analyze　of　the　plantar　pressure　data　and　identification　of　normal　or　abnormal　gait　is　done.　Based　on　actual　clinical　data,　this　method　carries　out　an　analysis　of　patients　with　anterior　cruciate　ligament　deficiency,　which　is　checked　according　to　the　doctor＇s　clinical　diagnosis　results.　Result　shows　that　this　method　is　effective.　Copyright　©　2017　Acta　Automatica　Sinica.　All　rights　reserved.