In this paper we consider the problem of identication of cough events in patients suffering from chronic respiratory diseases. The information about frequency of cough events is necessary to medical treatment. The proposed approach is based on bidirectional processing of a measured vibration signal - cough events are localized by combining the results of forward-time and backward-time analysis. The signal is at rst transformed using Daub4 wavelet in order to map it to its rst trend subsignal and rst uctuation subsignal. This enables us to localize cough events in the uctuation subsignal by tracking its instantaneous variance. The proposed approach allows to distinguish between cough and cough-like episodes (scream, speech etc). It is validated using recorded data including 271 events, both cough and non-cough events. 98% sensitivity, and 90% specicity were obtained.
Authors
Additional information
- Category
- Aktywność konferencyjna
- Type
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Language
- angielski
- Publication year
- 2013
