Automatic wheeze detection based on auditory modelling

Abstract Automatic wheeze detection has several potential benefits compared with reliance on human auscultation: it is experience independent, an automated historical record can easily be kept, and it allows quantification of wheeze severity. Previous attempts to detect wheezes automatically have had partial success but have not been reliable enough to become widely accepted as a useful tool. In this paper an improved algorithm for automatic wheeze detection based on auditory modelling is developed, called the frequency- and duration-dependent threshold algorithm. The mean frequency and duration of each wheeze component are obtained automatically. The detected wheezes are marked on a spectrogram. In the new algorithm, the concept of a frequency- and duration-dependent threshold for wheeze detection is introduced. Another departure from previous work is that the threshold is based not on global power but on power corresponding to a particular frequency range. The algorithm has been tested on 36 subjects, 11 of whom exhibited characteristics of wheeze. The results show a marked improvement in the accuracy of wheeze detection when compared with previous algorithms.

[1]  Hans Pasterkamp,et al.  Automated Spectral Characterization of Wheezing in Asthmatic Children , 1985, IEEE Transactions on Biomedical Engineering.

[2]  F. Dalmasso,et al.  Definition of terms for applications of respiratory sounds , 2000 .

[3]  J B Grotberg,et al.  Spectral content of forced expiratory wheezes during air, He, and SF6 breathing in normal humans. , 1992, Journal of applied physiology.

[4]  V Chernick,et al.  The effect of anticholinergic treatment on postexertional wheezing in asthma studied by phonopneumography and spirometry. , 1985, The American review of respiratory disease.

[5]  S. Qian,et al.  Joint time-frequency analysis : methods and applications , 1996 .

[6]  P. Escourrou,et al.  Intraction between tracheal sound and flow rate: a comparison of some different flow evaluations from lung sounds , 1990, IEEE Transactions on Biomedical Engineering.

[7]  Evon M. O. Abu-Taieh,et al.  Comparative Study , 2020, Definitions.

[8]  R. Beck,et al.  Histamine challenge in young children using computerized lung sounds analysis. , 1992, Chest.

[9]  Lawrence O'Gorman,et al.  Practical Algorithms for Image Analysis: Description, Examples and Code , 2000 .

[10]  Yihong Qiu,et al.  Measurement and analysis of breath sounds , 2003 .

[11]  Charlotte M. Reed,et al.  A comparative study of S/N0 and E/N0 , 1973 .

[12]  P Helistö,et al.  A new method for automatic wheeze detection. , 1998, Technology and health care : official journal of the European Society for Engineering and Medicine.

[13]  Raimon Jané,et al.  Detection of wheezing during maximal forced exhalation in patients with obstructed airways. , 2002, Chest.

[14]  R. Jane,et al.  Algorithm for time-frequency detection and analysis of wheezes , 2000, Proceedings of the 22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (Cat. No.00CH37143).

[15]  Douglas L. Jones,et al.  Signal-dependent time-frequency analysis using a radially Gaussian kernel , 1993, Signal Process..

[16]  Jessika Eichel,et al.  FUNDAMENTALS OF HEARING: AN INTRODUCTION , 1978, The Ulster Medical Journal.

[17]  J Schäfer,et al.  Posture-dependent change of tracheal sounds at standardized flows in patients with obstructive sleep apnea. , 1996, Chest.

[18]  Yihong Qiu,et al.  Breath sounds, asthma, and the mobile phone , 2001, The Lancet.

[19]  George R. Wodicka,et al.  Modeling and measurement of flow effects on tracheal sounds , 2003, IEEE Transactions on Biomedical Engineering.

[20]  R. Baughman,et al.  Lung sound analysis for continuous evaluation of airflow obstruction in asthma. , 1985, Chest.

[21]  M. Mussell,et al.  Effect of air flow and flow transducer on tracheal breath sounds , 1990, Medical and Biological Engineering and Computing.

[22]  R. Baughman,et al.  Stridor: differentiation from asthma or upper airway noise. , 1989, The American review of respiratory disease.

[23]  H. Pasterkamp,et al.  Subjective assessment vs computer analysis of wheezing in asthma. , 1987, Chest.

[24]  E. Owens,et al.  An Introduction to the Psychology of Hearing , 1997 .

[25]  H. Pasterkamp,et al.  Respiratory sounds. Advances beyond the stethoscope. , 1997, American journal of respiratory and critical care medicine.