2012
DOI: 10.1515/bmt-2012-4149
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On-line Learning Algorithms for extracting respiratory activity from Single Lead ECGs based on Principal Component Analysis

Abstract: In this paper we present several statistic gradient algorithms from literature to solve the Principal Component Analysis (PCA) problem. We used a linear artificial neural network forming the basis of the implemented algorithms which is a neat way for on-line computation of the PCA expansion. As convergence is a key-aspect of these algorithms and is crucial for the usefulness in particular applications, we compared the different learning rules with respect to their suitability in ECG signal processing. Recent s… Show more

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Cited by 1 publication
(1 citation statement)
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“…In [ 18 ], we have evaluated different learning algorithms in an attempt to extract respiratory activity out of single-lead ECGs acquired from the Physionet Database. As the results were quite promising, we decided to develop a new measurement system consisting of a wireless multichannel ECG sensor-module in combination with a piezo respiration belt sensor-module.…”
Section: Introductionmentioning
confidence: 99%
“…In [ 18 ], we have evaluated different learning algorithms in an attempt to extract respiratory activity out of single-lead ECGs acquired from the Physionet Database. As the results were quite promising, we decided to develop a new measurement system consisting of a wireless multichannel ECG sensor-module in combination with a piezo respiration belt sensor-module.…”
Section: Introductionmentioning
confidence: 99%