A Chaotic Viewpoint on Noise Reduction from Respiratory Sounds
Malihe Molaiea, S. Jafaria, M. H.
Moradia, J. C. Sprottb,
S. Mohammad Reza Hashemi Golpayegania
aDepartment of Biomedical Engineering, Amirkabir
University of Technology, 424 Hafez Avenue,Tehran 15875-4413,
bDepartment of Physics, University of Wisconsin--Madison,
Madison, WI 53706, USA
Received 20 July 2013, Received in revised form 2 October 2013,
Accepted 31 October 2013, Available online 4 December 2013
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
Ref: M. Molaie, S. Jafari, M. H. Moradi, J.
C. Sprott, and S. M. R. H. Golpayegani, Biomedical Signal
Processing and Control 10, 245-249 (2014)
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