The RR-interval time series or tachograms obtained from electrocardiograms have been widely studied since they reflect the cardiac variability, and this is an indicative of the health status of a person. The tachogram can be seen as a highly non-linear and complex time series, and therefore, should be analyzed with non-linear techniques. In this work, several entropy measures, Sample Entropy (SampEn), Approximate Entropy (ApEn), and Fuzzy Entropy (FuzzyEn) are used as a measure of heart rate variability (HRV). Tachograms belonging to thirty-nine subjects were obtained from a cardiac stress test consisting of a rest period followed by a period of moderate physical activity. Subjects are grouped according to their physical activity using the IPAQ sedentary and active questionnaire, we work with youth and middle-aged adults. The entropy measures for each group show that for the sedentary subjects the values are high at rest and decrease appreciably with moderate physical activity, This happens for both young and middle-aged adults. These results are highly reproducible. In the case of the subjects that exercise regularly, an increase in entropy is observed or they tend to retain the entropy value that they had at rest. It seems that there is a possible correlation between the physical condition of a person with the increase or decrease in entropy during moderate physical activity with respect to the entropy at rest. It was also observed that entropy during longer physical activity tests tends to decrease as fatigue accumulates, but this decrease is small compared to the change that occurs when going from rest to physical activity.

Abstract. In this paper a statistical analysis of seismoelectric ULF signals prior to the M7.4 Guerrero-Oaxaca earthquake (EQ) occurred at the Mexican Pacific coast on 14 September 1995, has been performed. The signals were simultaneously recorded at three monitoring stations from the last months of 1994 until July of 1996. The nonlinear time series methods of Higuchi fractal dimension (HFD) and detrended fluctuation analysis (DFA) have been used. In the three data sets we found some complex dynamical behaviors that seemingly reflect a relaxation-EQ preparation-main shock-relaxation process. In particular, clear spike-like anomalies in both DFAand HFD-exponents some months before the main shock are revealed.

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Abstract. Recent studies related with earthquake prediction involve statistical studies of the ground electric self-potential behavior. Published results about the complexity of this kind of processes encourage us to study the statistical behavior of the ground electric self-potential recorded in Guerrero state, Mexico. This region is characterized by high seismicity. The electric self-potential variations were recorded in the Acapulco station directly from the ground. The sampling period was four seconds and the data were stored from March to December of 1993. Two significant earthquakes (EQs) occurred near this station, 15 May and 24 October whose magnitudes were Mw=6.0 and Mw=6.6 respectively. A preliminary processing was carried out consisting of a moving average of the original time series in order to filter the very high frequencies and to complete short lacks of data and outliers. Then, a visual inspection of the complete filtered signal was performed to search some seismic electric signals (SES), which were ambiguously depicted. Subsequently, a detrending of µ=0 was applied with the windows of 3.3, 6.6 and 10 h. Later, the analysis of the spectral exponent β was made, showing changes during the total period examined, and the most evident changes occurred during the preparation mechanism of the Mw=6.6 EQ. Fifteen days before the 24 October EQ, a Brownian-noise like behavior was displayed (β≈2), having a duration of about two days. In addition a Higuchi fractal method and wavelet analysis were made confirming the presence of the β-anomaly.