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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
engineering
Multiparameter respiratory rate estimation from the photoplethysmogram
IEEE Transactions on Biomedical Engineering, Volume 60, No. 7, Article 6458992, Year 2013
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Description
We present a novel method for estimating respiratory rate in real time from the photoplethysmogram (PPG) obtained from pulse oximetry. Three respiratory-induced variations (frequency, intensity, and amplitude) are extracted from the PPG using the Incremental-Merge Segmentation algorithm. Frequency content of each respiratory-induced variation is analyzed using fast Fourier transforms. The proposed Smart Fusion method then combines the results of the three respiratory-induced variations using a transparent mean calculation. It automatically eliminates estimations considered to be unreliable because of detected presence of artifacts in the PPG or disagreement between the different individual respiratory rate estimations. The algorithm has been tested on data obtained from 29 children and 13 adults. Results show that it is important to combine the three respiratory-induced variations for robust estimation of respiratory rate. The Smart Fusion showed trends of improved estimation (mean root mean square error 3.0 breaths/min) compared to the individual estimation methods (5.8, 6.2, and 3.9 breaths/min). The Smart Fusion algorithm is being implemented in a mobile phone pulse oximeter device to facilitate the diagnosis of severe childhood pneumonia in remote areas. © 1964-2012 IEEE.
Authors & Co-Authors
Karlen, Walter
Canada, Vancouver
The University of British Columbia
South Africa, Stellenbosch
Stellenbosch University
Raman, Srinivas
Canada, Vancouver
The University of British Columbia
Ansermino, John Mark
Canada, Vancouver
The University of British Columbia
Dumont, Guy Albert M.
Canada, Vancouver
The University of British Columbia
Statistics
Citations: 374
Authors: 4
Affiliations: 2
Identifiers
Doi:
10.1109/TBME.2013.2246160
ISSN:
00189294
e-ISSN:
15582531
Research Areas
Health System And Policy
Maternal And Child Health