A chaotic viewpoint on noise reduction from respiratory sounds

Autor:	Julien Clinton Sprott, S. Mohammad Reza Hashemi Golpayegani, Sajad Jafari, Malihe Molaie, Mohammad Hasan Moradi
Rok vydání:	2014
Předmět:	Noise medicine.diagnostic_test Computer science Speech recognition Noise reduction Signal Processing Noise enhancement Chaotic medicine Health Informatics Respiratory sounds Impulse noise Dykstra's projection algorithm
Zdroj:	Biomedical Signal Processing and Control. 10:245-249
ISSN:	1746-8094
DOI:	10.1016/j.bspc.2013.10.009
Popis:	Analysis of respiratory sounds can help the recognition of various respiratory diseases. Due to acoustic noise in hospital environments, the recorded sounds are polluted. The noise can destroy the analysis and should therefore be removed. Because of the chaotic nature of respiratory sounds, traditional noise reduction methods may not be efficient. Thus taking advantage of algorithms especially devised for noise reduction from chaotic signals can lead to better results. In this paper, a new method based on an original local projection algorithm is presented to reduce the noise in respiratory sounds.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::2030716889286f666d9e04f0083a94e6 https://doi.org/10.1016/j.bspc.2013.10.009 Zobrazit plný text záznamu Full Text from ScienceDirect