title: [Application of the computer-based respiratory sound analysis system based on Mel-frequency cepstral coefficient and dynamic time warping in healthy children].
abstract: OBJECTIVE
  We designed a computer-based respiratory sound analysis system to identify pediatric normal lung sound. To verify the validity of the computer-based respiratory sound analysis system.
  
  
  METHODS
  First we downloaded the standard lung sounds from the network database (website: http: //www.easyauscultation.com/lung-sounds-reference-guide) and recorded 3 samples of abnormal loud sound (rhonchi, wheeze and crackles) from three patients of The Department of Pediatrics, the First Affiliated Hospital of Xiamen University. We regarded such lung sounds as"reference lung sounds". The"test lung sounds"were recorded from 29 children form Kindergarten of Xiamen University. we recorded lung sound by portable electronic stethoscope and valid lung sounds were selected by manual identification. We introduced Mel-frequency cepstral coefficient (MFCC) to extract lung sound features and dynamic time warping (DTW) for signal classification.
  
  
  RESULTS
  We had 39 standard lung sounds, recorded 58 test lung sounds. This computer-based respiratory sound analysis system was carried out in 58 lung sound recognition, correct identification of 52 times, error identification 6 times. Accuracy was 89.7%.
  
  
  CONCLUSIONS
  Based on MFCC and DTW, our computer-based respiratory sound analysis system can effectively identify healthy lung sounds of children (accuracy can reach 89.7%), fully embodies the reliability of the lung sounds analysis system.
authors: Department of Pediatrics, the First Affiliated Hospital of Xiamen University, Xiamen 361003, China.
authors: W Y
authors: WY
authors: Yan
authors: L
authors: L
authors: Li
authors: Y G
authors: YG
authors: Yang
authors: X L
authors: XL
authors: Lin
authors: J Z
authors: JZ
authors: Wu
mesh_terms: D000465:Algorithms; D001314:Auscultation; D002648:Child; D006801:Humans; D015203:Reproducibility of Results; D012135:Respiratory Sounds; D012815:Signal Processing, Computer-Assisted