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A Model to Simulate Clinically Relevant Hypoxia in Humans
Published on: December 22, 2016
Independent component analysis applied to pulse oximetry in the estimation of the arterial oxygen saturation
Thomas Jensen1, Sune Duun, Jan Larsen
1Department of Informatics and Mathematical Modeling, Technical University of Denmark, Richard Petersens Plads B321, 2800 Kgs. Lyngby, Denmark.
Abstract:
We examine various independent component analysis (ICA) digital signal processing algorithms for estimating the arterial oxygen saturation (SpO2) as measured by a reflective pulse oximeter. The ICA algorithms examined are FastICA, Maximum Likelihood ICA (ICAML), Molgedey and Schuster ICA (ICAMS), and Mean Field ICA (ICAMF). The signal processing includes pre-processing bandpass filtering to eliminate noise, and post-processing by calculating the SpO2. The algorithms are compared to the commercial state-of-the-art algorithm Discrete Saturation Transform (DST) by Masimo Corporation. It is demonstrated that ICAMS and ICAMF perform up to 13% better than DST. PPG recordings are done with a reflective pulse oximetry sensor integrated in an Electronic Patch. This system is intended for patients with chronic heart and lung conditions.
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