Key result
An optimally chosen fixed set of coefficients for the linear combination of different ECG derived respiration methods delivers a better estimation than each method used solely.
Combining different ECG derived respiration tracking methods using an optimal linear combination provides a more accurate estimation of the breathing pattern than individual methods.
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May enhance ECG respiration estimation accuracy; leaves open clinical utility pending prospective validation.
ECG derived respiration (EDR) is a technique applied to estimate the respiration signal using only the electrocardiogram (ECG). Different approaches have been proposed in the past on how respiration could be gained from the ECG. However, in many applications only one of them is used while the others are not considered at all. In this paper, we propose a new algorithm for the optimal linear combination of different EDR methods in order to create a more accurate estimation. Using two well known databases, it was statistically shown that an optimally chosen fixed set of coefficients for the linear combination delivers a better estimation than each of the methods used solely.
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Lenis et al. (2015) studied ECG derived respiration. Optimal linear combination of different EDR methods vs. Individual EDR methods used solely was evaluated on Accuracy of respiration signal estimation. An optimally chosen fixed set of coefficients for the linear combination of different ECG derived respiration methods delivers a better estimation than each method used solely.
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