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Volumn 13, Issue 5, 2009, Pages 810-817

Automatic recognition of gait patterns exhibiting patellofemoral pain syndrome using a support vector machine approach

Author keywords

Gait analysis; Ground reaction forces (GRFs); Kinematics; Patellofemoral pain syndrome (PFPS); Support vector machines (SVMs)

Indexed keywords

AGE GROUPS; AUTOMATED SYSTEMS; AUTOMATIC RECOGNITION; BIOMECHANICAL FACTORS; CLASSIFICATION ACCURACY; CLASSIFICATION PERFORMANCE; FEATURE SELECTION; FEATURE SETS; GAIT PARAMETERS; GAIT PATTERN; GROUND REACTION FORCES; GROUND REACTION FORCES (GRFS); HILL CLIMBING; KINETIC FEATURES; KNEE PAIN; LEAVE-ONE-OUT; OPTIMAL CLASSIFIERS; PATELLOFEMORAL PAIN SYNDROME (PFPS); PATELLOFEMORAL PAIN SYNDROMES; STATISTICAL ANALYSIS; STATISTICAL DIFFERENCES; TEST RESULTS;

EID: 70349427171     PISSN: 10897771     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITB.2009.2022927     Document Type: Article
Times cited : (58)

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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.