title: Classification of lung sounds during bronchial provocation using waveform fractal dimensions.
abstract: Lung sounds (LS) of children after bronchoconstriction should differ from baseline LS in terms of amplitude and pattern characteristics. To test these hypotheses, time-domain and fractal based analyses have been applied to LS acquired from eight children ages 9-15 y pre- and post-methacholine challenge (MCh). Change in forced expiratory volume in 1 s after MCh ranged from -4% to -37%, with change proportional to severity of bronchoconstriction. Sounds were recorded over the posterior right lower lung lobe while subjects breathed normally for 60 s with flow measurement, and during 10 s of breath hold (BH). From root-mean-square (RMS) of LS and BH signals, signal-to-noise ratio (SNR) was determined. Two fractal dimension (FD) algorithms were applied, based on signal variance and morphology. Feature vectors for 1-nearest-neighbor classification contained FD and RMS values within flow plateau ranges. Results for LS within 75-600 Hz indicate that the combination of RMS-SNR and morphology-based FD values offers better classification of bronchoconstriction with LS, relative to using RMS-SNR with variance-based FDs and RMS-SNR alone. True positive classification was 90.3%, 63.5% and 58.3% respectively, and false positive classification was 23.4%, 24.9% and 26.1% respectively. Both RMS-SNR and FD values provide useful insight into LS changes post-bronchoconstriction.
authors.affiliation: Department of Electrical Engineering, University of Manitoba, Winnipeg, MB, Canada.
authors.forename: J
authors.initials: J
authors.lastname: Gnitecki
authors.forename: Z
authors.initials: Z
authors.lastname: Moussavi
authors.forename: H
authors.initials: H
authors.lastname: Pasterkamp