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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Biomedical Signal Pr...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Biomedical Signal Processing and Control
Article . 2013 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
DBLP
Article . 2020
Data sources: DBLP
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Interstitial fluid glucose time-lag correction for real-time continuous glucose monitoring

Authors: D. Barry Keenan; John J. Mastrototaro; Stuart Weinzimer; Garry M. Steil;

Interstitial fluid glucose time-lag correction for real-time continuous glucose monitoring

Abstract

Abstract Time lag between subcutaneous interstitial fluid and plasma glucose decreases the accuracy of real-time continuous glucose monitors. However, inverse filters can be designed to correct time lag and attenuate noise enabling the blood–glucose profile to be reconstructed in real time from continuous measurements of the interstitial-fluid glucose. We designed and tested a Wiener filter using a set of 20 sensor-glucose tracings (∼30 h each) with a 1-min sample interval. Delays of 10 ± 2 min (mean ± SD) were introduced into each signal with additive Gaussian white noise (SNR = 40 dB). Performance of the filter was compared to conventional causal and non-causal seventh-order finite-impulse response (FIR) filters. Time lags introduced an error of 5.3 ± 2.7%. The error increased in the presence of noise (to 5.7 ± 2.6%) and attempts to remove the noise with conventional low-pass filtering increased the error still further (to 7.0 ± 3.5%). In contrast, the Wiener filter decreased the error attributed to time delay by ∼50% in the presence of noise (from 5.7% to 2.60 ± 1.26%) and by ∼75% in the absence of noise (5.3% to 1.3 ± 1%). Introducing time-lag correction without increasing sensitivity to noise can increase CGM accuracy.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
32
Top 10%
Top 10%
Top 10%
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