Title :
WED: An efficient wheezing-episode detector based on breath sounds spectrogram analysis
Author :
Taplidou, S.A. ; Hadjileontiadis, L.J. ; Penzel, T. ; Gross, V. ; Panas, S.M.
Author_Institution :
Dept. of Electr. & Comput. Eng., Aristotelian Univ. of Thessaloniki, Greece
Abstract :
An enhanced method for the detection of wheezes, based on the spectrogram of the breath sound recordings is proposed. The identification of wheezes in the total breath cycle would contribute to the diagnosis of pathologies related to patients with obstructive airway diseases. Fast and quite simple techniques are applied to automatically locate and identify wheezing-episodes. Amplitude criteria are applied to the peaks of the spectrogram in order to discriminate the wheezing from the breath sound, whereas frequency and time continuity criteria are used to improve the results. The proposed detector could be used for long-term wheezing screening in sleep-laboratories, resulting in significant data-volume reduction.
Keywords :
bioacoustics; biomedical measurement; diseases; patient diagnosis; pneumodynamics; spectral analysis; automatic location; breath sounds spectrogram analysis; data-volume reduction; efficient wheezing-episode detector; frequency continuity criteria; long-term wheezing screening; obstructive airway diseases; pathologies diagnosis; sleep-laboratories; time continuity criteria; total breath cycle; Acoustical engineering; Detectors; Diseases; Frequency conversion; Frequency domain analysis; Laboratories; Lungs; Medical diagnostic imaging; Pathology; Spectrogram;
Conference_Titel :
Engineering in Medicine and Biology Society, 2003. Proceedings of the 25th Annual International Conference of the IEEE
Print_ISBN :
0-7803-7789-3
DOI :
10.1109/IEMBS.2003.1280431