Overcomplete discrete wavelet transform based respiratory sound discrimination with feature and decision level fusion

Ulukaya S., SERBES G., Kahya Y. P.

BIOMEDICAL SIGNAL PROCESSING AND CONTROL, vol.38, pp.322-336, 2017 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 38
  • Publication Date: 2017
  • Doi Number: 10.1016/j.bspc.2017.06.018
  • Journal Name: BIOMEDICAL SIGNAL PROCESSING AND CONTROL
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.322-336
  • Keywords: Pulmonary sound, Rational dilation wavelet transform, Q-factor, Ensemble learning, Adventitious lung sounds, Statistical feature extraction, NEURAL-NETWORK, LUNG SOUNDS, CLASSIFICATION, FREQUENCY
  • Yıldız Technical University Affiliated: Yes

Abstract

Background and objective: Crackle, wheeze and normal lung sound discrimination is vital in diagnosing pulmonary diseases. Previous works suffer from limited frequency resolution and lack of the ability to deal with oscillatory signals (wheezes). The main objective of this study is to propose a novel wavelet based lung sound classification system that is capable of adaptively representing crackle, wheeze and normal lung sound signal time-frequency properties.