Effects of functional training on geometric indices of heart rate variability

Abstract

BackgroundGeometric methods provide an analysis of autonomic modulation using the geometric properties of the resulting pattern, and represent an interesting tool in the analysis of heart rate variability (HRV). The aim of this study was to evaluate the impact of functional training on cardiac autonomic modulation in healthy young women using the geometric indices of HRV.MethodsData were analyzed from 29 women, and were stratified into a functional training group (FTG, n = 13; 23.00 ± 2.51 years; 21.90 ± 2.82 kg/m2) and a control group (CG, n = 16; 20.56 ± 1.03 years; 22.12 ± 3.86 kg/m2). The FTG received periodized functional training for 12 weeks. The cardiac autonomic modulation of both groups was evaluated before and after this training, and a qualitative analysis was performed using the Poincaré plot.ResultsThere was a significant increase in the difference of the triangular index (RRTri), SD1, SD2, and RR intervals in the FTG as compared to the CG, and the qualitative analysis from the Poincaré plot showed an increase in the dispersion of beat-to-beat and long-term RR intervals in the functional group after training. No changes were observed in the triangular interpolation of RR interval histogram (TINN) or SD1/SD2.ConclusionFunctional training had a beneficial impact on autonomic modulation, as characterized by increased parasympathetic activity and overall variability, thus highlighting the clinical usefulness of this type of training.

Functional training in postmenopause: Cardiac autonomic modulation and cardiorespiratory parameters, a randomized trial

“…Studies evaluating functional resistance training for 12 weeks in young healthy women showed improvement in quality of life and cardiac autonomic modulation . In the study of Rezende Barbosa et al was observed an increasing the values of RMSSD, SDNN, RR intervals, LFms 2 and HFms 2 ; whereas in another study by Rezende Barbosa et al , an increase was observed in the values of RRtri index, SD1, SD2 and RR intervals …”

“…The movement of people on the site was restricted, in order to reduce interference during collection. The volunteers were asked abstain from consuming alcohol and/or stimulants, such as coffee, tea and chocolate drinks, 24 h before the evaluation …”

Impact of functional training on geometric indices and fractal correlation property of heart rate variability in postmenopausal women

“…Changes in heart rate defined as heart rate variability (HRV) are normal and expected and indicate a heart's ability to respond to multiple physiological and environmental stimuli as well as to compensate disorders induced by diseases (Silva et al., ; Vanderlei et al., ) . HRV is a simple and not invasive tool that describes the fluctuations between the consecutive heart beats intervals (RR Intervals) and can be used to identify phenomena related to the autonomic nervous system (ANS) (De Rezende Barbosa et al., 2016a,b; Silva et al., ; Vanderlei et al., Giacon et al, ).…”

“…Among the linear methods that assess HRV we highlight the geometric indices (triangular index [RRtri], triangular interpolation of RR interval histogram [TINN] and Poincaré plot) which convert RR intervals into geometric patterns and allow analyzing HRV through the geometric or graphic properties of the resulting pattern (De Rezende Barbosa et al., 2016a,b; Hoshi et al., , Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology ; Vanderlei et al., ).…”

“…However, considering the nonlinear nature of the body systems, HRV analysis by nonlinear methods has been gaining increasing interest (Boettger et al., ; De Rezende Barbosa et al., 2016a,b; Hoshi et al., ). These methods have shown a new vision on heart rate (HR) behavior abnormalities in various conditions, providing information to physiological and additional prognostic interpretations when compared to traditional methods (Boettger et al., ; De Rezende Barbosa et al., 2016a,b; Godoy, Takakura, & Correa, ; Khaled, Owis, & Mohamed, ). Therefore, nonlinear analysis of HRV is also necessary because information can be lost if only linear analyses are applied (Hoshi et al., , Task Force of the European Society of Cardiology, the North American Society of Pacing and Electrophysiology, ).…”