New non-invasive automatic cough counting program based on 6 types of classified cough sounds

Abstract

Cough consisting of an initial deep inspiration, glottal closure, and an explosive expiration accompanied by a sound is one of the most common symptoms of respiratory disease. Despite its clinical importance, standard methods for objective cough analysis have yet to be established.

Object: We investigated the characteristics of cough sounds acoustically, designed a program to discriminate cough sounds from other sounds, and finally developed a new objective method of non-invasive cough counting. In addition, we evaluated the clinical efficacy of that program.

Subjects and methods: We recorded cough sounds using a memory stick IC recorder in free-field from 2 patients and analyzed the intensity of 534 recorded coughs acoustically according to time domain. First we squared the sound waveform of recorded cough sounds, which was then smoothed out over a 20 ms window. The 5 parameters and some definitions to discriminate the cough sounds from other noise were identified and the cough sounds were classified into 6 groups. Next, we applied this method to develop a new automatic cough count program. Finally, to evaluate the accuracy and clinical usefulness of this program, we counted cough sounds collected from another 10 patients using our program and conventional manual counting. And the sensitivity, specificity and discriminative rate of the program were analyzed.

Results: This program successfully discriminated recorded cough sounds out of 1902 sound events collected from 10 patients at a rate of 93.1%. The sensitivity was 90.2% and the specificity was 96.5%.

Conclusion: Our new cough counting program can be sufficiently useful for clinical studies.