2011 IEEE International Conference on Information and Automation 2011
DOI: 10.1109/icinfa.2011.5949053
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Multi-Gaussian fitting for Digital Volume Pulse using Weighted Least Squares method

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Cited by 7 publications
(1 citation statement)
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“…16 Meanwhile, the similarity of a single hemodynamic wave component, i.e., the left ventricle ejection volume profile and the Gaussian function profile, has previously been reported and utilized 17,18 and can also be visually noticed. 19 Recent studies employ a multi-Gaussian model for fitting the peripheral pulse waveform [20][21][22] guided by the criterion of minimal root-mean-square error (RMSE). An approximation of the SPPPG waveform with four Gaussian functions has also been demonstrated by our group highlighting its advantages over the derivative analysis.…”
Section: Introductionmentioning
confidence: 99%
“…16 Meanwhile, the similarity of a single hemodynamic wave component, i.e., the left ventricle ejection volume profile and the Gaussian function profile, has previously been reported and utilized 17,18 and can also be visually noticed. 19 Recent studies employ a multi-Gaussian model for fitting the peripheral pulse waveform [20][21][22] guided by the criterion of minimal root-mean-square error (RMSE). An approximation of the SPPPG waveform with four Gaussian functions has also been demonstrated by our group highlighting its advantages over the derivative analysis.…”
Section: Introductionmentioning
confidence: 99%