Literature DB >> 8332005

Acoustic analysis of infantile stridor: a review.

M Malone1, N D Black, M Lydon, M Cinnamond.   

Abstract

The review compares five methods that utilise electronic/computer acoustic processing techniques for the analysis of infantile stridor sounds. The first method uses traditional spectrographic techniques to produce time/frequency/intensity three-dimensional representation of the waveform. The second method is computer-based and uses the fast Fourier transformation (FFT) to show the frequency composition of the waveform. The third uses linear prediction coefficients (LPCs) to produce a power spectrum and inverse filtering to estimate the cross-sectional area of the human upper airway. The fourth technique employs a proprietary digital filterbank to analyse normal infant vocalisations, which may be used as a control by subsequent researchers. In the fifth method, a physiologically based digital filterbank, designed to closely model the human ear response, is proposed. It is envisaged that this approach will offer the flexibility of all the previous techniques and also closely model the analysis procedure carried out using subjective auscultation. It is concluded that none of the above techniques are sufficiently robust to provide unambiguous diagnosis of stridor type and that a reappraisal is required in terms of feature extraction so that relevant features can be identified. To this end, the authors propose that a physiologically based model of the human airway, including the vocal cords, be developed as an aid to the assessment of acoustic features.

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Year:  1993        PMID: 8332005     DOI: 10.1007/bf02446665

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  17 in total

1.  Model for wave propagation in a lossy vocal tract.

Authors:  M M Sondhi
Journal:  J Acoust Soc Am       Date:  1974-05       Impact factor: 1.840

2.  Two-mass models of the vocal cords for natural sounding voice synthesis.

Authors:  T Koizumi; S Taniguchi; S Hiromitsu
Journal:  J Acoust Soc Am       Date:  1987-10       Impact factor: 1.840

3.  Spectral analysis of periodic and normal breathing in infants.

Authors:  S T Nugent; J P Finley
Journal:  IEEE Trans Biomed Eng       Date:  1983-10       Impact factor: 4.538

4.  Analysis and automatic classification of breath sounds.

Authors:  A Cohen; D Landsberg
Journal:  IEEE Trans Biomed Eng       Date:  1984-09       Impact factor: 4.538

5.  Parameterization of the glottal area, glottal flow, and vocal fold contact area.

Authors:  I R Titze
Journal:  J Acoust Soc Am       Date:  1984-02       Impact factor: 1.840

6.  Inversion of articulatory-to-acoustic transformation in the vocal tract by a computer-sorting technique.

Authors:  B S Atal; J J Chang; M V Mathews; J W Tukey
Journal:  J Acoust Soc Am       Date:  1978-05       Impact factor: 1.840

7.  The diagnostic value of pulmonary sounds: a preliminary study by computer-aided analysis.

Authors:  R B Urquhart; J McGhee; J E Macleod; S W Banham; F Moran
Journal:  Comput Biol Med       Date:  1981       Impact factor: 4.589

8.  Digital spectrum analysis of respiratory sound.

Authors:  S K Chowdhury; A K Majumder
Journal:  IEEE Trans Biomed Eng       Date:  1981-11       Impact factor: 4.538

9.  Auscultation of the lung: past lessons, future possibilities.

Authors:  R L Murphy
Journal:  Thorax       Date:  1981-02       Impact factor: 9.139

10.  Digital signal processing of stridor and snoring in children.

Authors:  A Leiberman; A Cohen; A Tal
Journal:  Int J Pediatr Otorhinolaryngol       Date:  1986-12       Impact factor: 1.675

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