ObjectivesClinical and experimental research studies have demonstrated that the emotional experience of anxiety impairs heart rate variability (HRV) in humans. The present study investigated whether changes in state anxiety (SA) can also modulate nonlinear dynamics of heart rate.MethodsA group of 96 students volunteered to participate in the study. For each student, two 5-minute recordings of beat intervals (RR) were performed: one during a rest period and one just before a university examination, which was assumed to be a real-life stressor. Nonlinear analysis of HRV was performed. The Spielberger’s State-Trait Anxiety Inventory was used to assess the level of SA.ResultsBefore adjusting for heart rate, a Wilcoxon matched pairs test showed significant decreases in Poincaré plot measures, entropy, largest Lyapunov exponent (LLE), and pointwise correlation dimension (PD2), and an increase in the short-term fractal-like scaling exponent of detrended fluctuation analysis (α1) during the exam session, compared with the rest period. A Pearson analysis indicated significant negative correlations between the dynamics of SA and Poincaré plot axes ratio (SD1/SD2), and between changes in SA and changes in entropy measures. A strong negative correlation was found between the dynamics of SA and LLE. A significant positive correlation was found between the dynamics of SA and α1. The decreases in Poincaré plot measures (SD1, complex correlation measure), entropy measures, and LLE were still significant after adjusting for heart rate. Corrected α1 was increased during the exam session. As before, the dynamics of adjusted LLE was significantly correlated with the dynamics of SA.ConclusionsThe qualitative increase in SA during academic examination was related to the decrease in the complexity and size of the Poincaré plot through a reduction of both the interbeat interval and its variation.

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IntroductionThis study investigates the variations of nonlinear parameters of heart rate variability (HRV) due to an arithmetic stress test.Material and methodsWe tested 83 healthy students with a mean age of 21.12±0.21 years. The students were examining in the following sequence: recording of HRV at rest and during mental arithmetic. HRV was assessed by applying Poincare plot analysis (SD1, SD2, SD2/SD1, SS) to the R‐R interval series on a 10‐min ECG. The traditional (GI) and redefined Guzik's index (GIp) (Karmakar, 2010) was calculated for each subjects in each phase of the experiments.Results and discussionSD1 during mental arithmetic was significantly smaller (24.51±1.77) than that at rest (34.57±2.05; p<0.0001). SD1/SD2 ratio during mental stress was significantly lower than that at rest (0.331±0.013 vs 0.469±0.017; p<0.00001). SS was significantly lower during the test than that at rest (2756.13±313.97 vs 3822.66±370.57; p=0.008). There was no significant difference in the GI during mental stress (0.495±0.008) than that at rest (0.485±0.005; p>0.05). But after redefinition, we have found pronounced changes in this parameter with a maximum at rest day and minimum during arithmetic test (0.446±0.024 vs 0.398±0.018; p<0.05).This findings suggest that nonlinear HRV analysis could be effective in automatically detecting functional status during mental stress.

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