Signal feature extraction by multi-scale PCA and its application to respiratory sound classification

Medical and Biological Engineering and Computing

Volumn 50, Issue 7, 2012, Pages 759-768

  Xie, Shengkun ^a   Jin, Feng ^a   Krishnan, Sridhar ^a   Sattar, Farook ^b  

^a RYERSON UNIVERSITY   (Canada)

^b UNIVERSITY OF VICTORIA   (Canada)

Author keywords

Multi scale principal component analysis; Respiratory sound; Signal classification; Signal variability

Indexed keywords

ADVENTITIOUS SOUNDS; CLASSIFICATION METHODS; FEATURE EXTRACTION METHODS; FOURIER; HIGH DIMENSIONAL FEATURE; MULTI SCALE ANALYSIS; MULTI-SCALE PRINCIPAL COMPONENT ANALYSIS; MULTISCALES; POWER-SPECTRA; RESPIRATORY SOUNDS; SIGNAL CLASSIFICATION; SIGNAL DIMENSIONS; SIGNAL ENHANCEMENT; SIGNAL VARIABILITY;

FEATURE EXTRACTION;

PRINCIPAL COMPONENT ANALYSIS;

ABNORMAL RESPIRATORY SOUND; ADOLESCENT; ADULT; ARTICLE; CHILD; CLASSIFICATION; FEMALE; HUMAN; INFANT; LUNG DISEASE; MALE; MEDICAL ERROR; PHYSIOLOGY; PRESCHOOL CHILD; PRINCIPAL COMPONENT ANALYSIS; SIGNAL PROCESSING;

ADOLESCENT; ADULT; CHILD; CHILD, PRESCHOOL; FEMALE; HUMANS; INFANT; LUNG DISEASES; MALE; MEDICAL ERRORS; PRINCIPAL COMPONENT ANALYSIS; RESPIRATORY SOUNDS; SIGNAL PROCESSING, COMPUTER-ASSISTED; YOUNG ADULT;

EID: 84864363347     PISSN: 01400118     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11517-012-0903-y     Document Type: Article

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