An enhanced algorithm for knee joint sound classification using feature extraction based on time-frequency analysis

Computer Methods and Programs in Biomedicine

Volumn 94, Issue 2, 2009, Pages 198-206

  Kim, Keo Sik ^a   Seo, Jeong Hwan ^b   Kang, Jin U ^c   Song, Chul Gyu ^a,c  

^a Chonbuk National University   (South Korea)

^b Chonbuk National University Medical School   (South Korea)

^c Johns Hopkins University   (United States)

Author keywords

Articular pathology; Back propagation neural network; Singular value decomposition; Time frequency distribution; Vibroarthrography

Indexed keywords

ARTICULAR PATHOLOGY; BACK-PROPAGATION NEURAL NETWORK; CHARACTERISTIC PARAMETERS; CLASSIFICATION ACCURACIES; DE-NOISING ALGORITHMS; DYNAMIC TIME WARPING; ENERGY SPREADS; HUMAN KNEES; KNEE-JOINT SOUNDS; MULTI COMPONENTS; NON STATIONARIES; NON-INVASIVE DIAGNOSIS; ON TIME; STANDARD DEVIATIONS; TIME-FREQUENCY DISTRIBUTION; VIBROARTHROGRAPHY;

BACKPROPAGATION; BRIDGE PIERS; FEATURE EXTRACTION; FORESTRY; JOINTS (ANATOMY); NEURAL NETWORKS; PATHOLOGY; TORSIONAL STRESS;

SINGULAR VALUE DECOMPOSITION;

ADULT; ALGORITHMS; CARTILAGE, ARTICULAR; FEMALE; HUMANS; KNEE JOINT; MALE; MIDDLE AGED; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER); OSTEOARTHRITIS; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SIGNAL PROCESSING, COMPUTER-ASSISTED; TIME FACTORS;

EID: 61449166852     PISSN: 01692607     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cmpb.2008.12.012     Document Type: Article

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