The study investigates the nonlinear heart rate variability indices in different seasons and their dependence on current meteorological factors. The study included 61 relatively healthy student volunteers, their age w...The study investigates the nonlinear heart rate variability indices in different seasons and their dependence on current meteorological factors. The study included 61 relatively healthy student volunteers, their age were 19-23 and they were examined repeatedly in different seasons. The HRV （heart rate variability） recording was performed with the use of the hardware-software complex ＂Varikard 2.51＂ Nonlinear HRV indices were calculated by means of the Kubios HRV 2.1. The following indicators： SD1, SD2, SD1/SD2, D2, DFA, SampEn and quantitative indicators of recurrence analysis （RQA ）---Lmean, Lmax, REC, DET, ShanEn had been analyzed. Statistical analysis was performed using the Statistica 6.0. For the detection of between-group differences were used Repeated Measures ANOVA, and the dependence of nonlinear HRV indices on meteorological was analyzed with the use of multiple non-linear regression. The investigation showed a relative increase in SampEn and the reduction of al in winter and spring seasons, strengthening relationships SampEn correlation with other indicators in the winter season as well as the dependence SampEn on meteorological factors in summer. The detected changes can be considered as the realization of adaptive response of a healthy body.展开更多
文摘The study investigates the nonlinear heart rate variability indices in different seasons and their dependence on current meteorological factors. The study included 61 relatively healthy student volunteers, their age were 19-23 and they were examined repeatedly in different seasons. The HRV （heart rate variability） recording was performed with the use of the hardware-software complex ＂Varikard 2.51＂ Nonlinear HRV indices were calculated by means of the Kubios HRV 2.1. The following indicators： SD1, SD2, SD1/SD2, D2, DFA, SampEn and quantitative indicators of recurrence analysis （RQA ）---Lmean, Lmax, REC, DET, ShanEn had been analyzed. Statistical analysis was performed using the Statistica 6.0. For the detection of between-group differences were used Repeated Measures ANOVA, and the dependence of nonlinear HRV indices on meteorological was analyzed with the use of multiple non-linear regression. The investigation showed a relative increase in SampEn and the reduction of al in winter and spring seasons, strengthening relationships SampEn correlation with other indicators in the winter season as well as the dependence SampEn on meteorological factors in summer. The detected changes can be considered as the realization of adaptive response of a healthy body.
