The　sEMG　signals　are　collected　from　the　vastus　lateralis,　vastus　medialis,　biceps　femoris,　and　semitendinosus　of　lower　extremity　during　level　walking　among　control　subjects　and　knee　osteoarthritis　(OA)　patients,　the　latter　including　mild,　moderate　and　severe　degree.　The　5-fold　cross-validation　is　used　to　measure　the　accuracy　of　the　proposed　analysis　algorithm　on　collected　sEMG　recordings.　For　comparison,　the　more　classical　feature　vectors　of　form　factor,　degree　of　skewness,　kurtosis,　and　wavelet　entropy　are　also　tested.　In　experiment,　the　normalized　energy　ratio　and　marginal　spectrum　ratio　achieve　larger　accuracy　than　the　other　features　for　all　the　four　muscular　groups.　Moreover　the　accuracy　of　vastus　medialis　and　biceps　femoris　are　larger　than　that　of　vastus　lateralis　and　semitendinosus.　These　results　suggest　that　the　normalized　energy　ratio　and　marginal　spectrum　ratio　via　the　analysis　of　knee　sEMG　signals　by　HHT　can　server　as　characteristic　parameters　to　easily　classify　osteoarthritis　with　noninvasive　method.　The　more　important　muscular　groups　for　maintaining　the　knee　joint　function　are　medialis　and　biceps　femoris;　as　a　result　of　that　they　should　be　exercise　especially　for　rehabilitation.