Title :
Modified clustering algorithm for the trachea sound featuring
Author :
Hsueh, Meng-Lun ; Wu, Yu-Cheng ; Chong, Fok-Ching ; Lu, Bing-Yuh ; Wei, Shui-Ken ; Wu, Huey-Dong
Author_Institution :
Dept. of Electron. Eng., Nat. Taiwan Univ., Taipei, Taiwan
Abstract :
This study attempts to detect wheeze with k-means clustering algorithm. The subjects which included normal and wheeze sounds were evaluated. The algorithm presented a good performance to filter out noise and segment wheeze episode regions in the spectrograms. The results show that the clustering algorithm improved the signal-to-noise-ratio (SNR) from 29.02 ± 8.65 to 30.49 ± 9.01 dB in the cases of normal subjects, and 36.99 ± 9.67 to 38.29 ± 10.10 dB in the ones of wheeze subjects.
Keywords :
acoustic signal detection; pattern clustering; k-means clustering algorithm; modified clustering algorithm; signal-to-noise-ratio; spectrograms; trachea sound featuring; wheeze detection; Biology; Indexing; Nickel; Signal to noise ratio; SNR; filter; k-means clustering; segment; spectrogram; wheeze sounds;
Conference_Titel :
System Science and Engineering (ICSSE), 2010 International Conference on
Conference_Location :
Taipei
Print_ISBN :
978-1-4244-6472-2
DOI :
10.1109/ICSSE.2010.5551745
