By taking the value of SampEn(2, 0.2) as the distinguishing characteristic, it was possible to segment between the C and NC AEGM records significantly, with a p-value< 0.001.
Even though distributions were not statistically normal, the 95% confidence intervals given by [p [+ or -] 2[sigma]], where [mu] is SampEn mean and [sigma] is its standard deviation, do not overlap: [0.193, 0.199] for neither NC nor [0.216, 0.223] C AEGM.
Figure 4 depicts the influence that the inclusion of random spikes in AEGM signals had on SampEn values.
Table 1 shows, for different [p.sub.s], the numerical results related to the characterisation of the C and NC AEGM signals entropy at different spike perturbation levels.
Figure 6 shows the behaviour of SampEn when AEGM undergo distributed random sample loss.
Table 2 shows, for the different [eta] values, the numerical results related to the characterisation of the C and NC AEGM signals entropy at different distributed random loss levels.
Figure 8 shows the evolution of SampEn values for NC and C AEGM when consecutive sample loss takes place.
Thus SampEn is an appropriate measure to quantify the system complexity of AEGM signals, even with a short record length of 1.5s only.
The influence of spikes on the entropy of AEGM signals was characterised and quantified using synthetic spike trains added to the original signals.
Figure 8 and Table 3 confirmed this expected behaviour, but with complexity of C signals slightly decreasing for the sample loss ratios higher than 15%,which is the same ratio as in , and with the same SampEn parameters, despite dealing with AEGM signals instead.
This study addressed the regularity characterisation of the AEGM signals recorded in RFA procedures of AF and their associated SampEn.
(i) SampEn is an appropriate regularity measure for AEGM signals as it enables the robust segmentation between C and NC regions.