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Wavelet power spectrum from the continuous wavelet transform (CWT) of the entire time series from Pig 1. The plot depicts the presence of distinct periods throughout the time series, with the time in the experiment in seconds at the abscissa, the time of the respective periods on a logarithmic scale at the ordinate, and the "power" of distinct periods as a function of the time-series shown in colours according to the scale next to the plots. The CWT covering the whole range of periods from 30-10000 sec only reveals the slow oscillation at approximately 8000 sec (A), which is highlighted when focusing in on the slow periods (B). The CWT of the whole timeseries focusing on the high-frequency oscillations at 30-300 sec does not yield any meaningful result (C). https://doi.org/10.1371/journal.pone.0194826.g002 

Wavelet power spectrum from the continuous wavelet transform (CWT) of the entire time series from Pig 1. The plot depicts the presence of distinct periods throughout the time series, with the time in the experiment in seconds at the abscissa, the time of the respective periods on a logarithmic scale at the ordinate, and the "power" of distinct periods as a function of the time-series shown in colours according to the scale next to the plots. The CWT covering the whole range of periods from 30-10000 sec only reveals the slow oscillation at approximately 8000 sec (A), which is highlighted when focusing in on the slow periods (B). The CWT of the whole timeseries focusing on the high-frequency oscillations at 30-300 sec does not yield any meaningful result (C). https://doi.org/10.1371/journal.pone.0194826.g002 

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It is well-known that blood glucose oscillates with a period of approximately 15 min (900 s) and exhibits an overall complex behaviour in intact organisms. This complexity is not thoroughly studied, and thus, we aimed to decipher the frequency bands entailed in blood glucose regulation. We explored high-resolution blood glucose time-series sampled...

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Context 1
... removed the first 200 min of the sampled data in each series since these were periods of large instability and calibration of the sensors. The rest of the data from the entire study time until sacrifice of the animals are included in the study and are presented in Fig 1. The rest of the data were imported into the statistical soft- ware, and a combination of visual inspections and quantitative time-frequency analysis with continuous wavelet analysis was applied, as described in the Results & Discussion section. ...
Context 2
... recordings were mainly performed with BGLs in the range of 4 to 6.5 mmol/l; however, as seen from Fig 1, the BGLs of all animals slowly declined throughout the studies. Some of the BGLs of the animals were very low at the end of the experiment, and the data for these periods were discarded before analysis. ...
Context 3
... of the BGLs of the animals were very low at the end of the experiment, and the data for these periods were discarded before analysis. When qualitatively studying the BGLs of the four animals (Fig 1) a few oscillatory periods can clearly be seen. In Pig 1 and to some extent in Pig 3, one can see a very slow wave with a period of somewhere between 5000 and 10000 sec (0.0001-0.0002 ...
Context 4
... seen from Fig 1, Pig 2 had very distinct oscillations with a periodicity of some 1000 sec throughout the second quarter of the time series. We therefore specifically searched for this component in this one animal to quantify this component, looking in the range from 500 to 2000 sec. ...
Context 5
... have been some concerns that the observed differences in complexity in continu- ous glucose measurements in different clinical situations could be caused by limitations in the sensors [20]. However, the novel sensing system used in this study has a very low signal-to- noise ratio, as seen in the figures containing unprocessed raw data (Figs 1, 5, 7 and 8). The high-frequency phenomenon is unlikely to have been picked up with slower glucose sensors. ...

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... Indeed, oscillatory BG phenomena in the range of 0.01 to 0.02 Hz have been recently shown in the pig [58]. Thus, it would be of importance to confirm that calculations on nonsmoothed signals could account for improved accuracy and more informative complexity analysis. ...
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