Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICICS.2011.6173565
Title: A signal-noise separation algorithm for the estimation of respiratory rate from breath sound
Authors: Lin, I.
Ser, W.
Zhang, J.
Goh, D. 
Keywords: breath sound analysis
mean squre error
respiratory rate estimation
Issue Date: 2011
Abstract: Breathing is an involuntary action by the human body, and irregularities in breathing suggests possible respiratory disorders. Respiratory rate is an important parameter for breath sound analysis, and many papers have been published on how respiratory rate can be measured accurately and non-invasively. However, relatively fewer papers deal with breath sound based respiratory rate estimation. This paper proposes a signal-noise separation algorithm for estimating the respiratory rate from the breath sound. The estimation accuracy, in terms of mean square error, of the proposed algorithm has been evaluated using data collected from patients of the National University Hospital (NUH), for both low noise and high noise environments. © 2011 IEEE.
Source Title: ICICS 2011 - 8th International Conference on Information, Communications and Signal Processing
URI: http://scholarbank.nus.edu.sg/handle/10635/125722
ISBN: 9781457700309
DOI: 10.1109/ICICS.2011.6173565
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.