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Fig 1.

Trajectories of summed duration of 100 RR intervals.

Before (abscissa) and after (ordinate) an observed sliding RR interval (in seconds) in trained (red) and untrained (blue) subjects at (a) supine rest, (b) running and (c) relaxation. Arrows indicate the direction of movement of shorter RR intervals; (b) entering the analysis and (c) exiting the analysis. Note different scales of both axes in different states.

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Fig 1 Expand

Fig 2.

Examples of matrices of Pearson’s coefficients r(j, k).

(a) in one trained subject and (b) one untrained subject. In both examples, lower matrices were obtained at supine rest, middle at relaxation and upper at running.

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Fig 2 Expand

Table 1.

Comparison of SDRR and NAI between three physiological conditions in groups of untrained and trained subjects.

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Table 1 Expand

Fig 3.

Bar graphs show (a) SDRR—standard deviation of RR interval series and (b) NAInormalized asymmetry index. Data are presented as mean with standard errors. Statistical comparison of mean values between untrained and trained subjects during supine rest, running and relaxation.

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Fig 3 Expand

Fig 4.

Distribution of pooled local maxima of Pearson's correlation coefficients matrices (max r(j, k)) in trained subjects at supine rest (blue), running (red) and relaxation (green). (a) projected on the (j,k) plane, (b) plotted in 3D.

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Fig 4 Expand

Fig 5.

Distribution of pooled local maxima of Pearson's correlation coefficients matrices (max r(j, k)) in untrained subjects at supine rest (blue), running (red) and relaxation (green). (a) projected on the (j,k) plane, (b) plotted in 3D.

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Fig 5 Expand