Correcting the Activity-Specific Component of Heart Rate Variability Using Dynamic Body Acceleration Under Free-Moving Conditions.

Kazato Oishi,Masafumi Miwa,Hiroyuki Hirooka,Kaho Kitajima,Yudai Yasunaka,Yukiko Himeno,Hiroki Anzai,Seiji Ieiri,Hajime Kumagai

doi:10.3389/fphys.2018.01063

Abstract

Heart rate variability (HRV) analysis is a widely used technique to assess sympatho-vagal regulation in response to various internal or external stressors. However, HRV measurements under free-moving conditions are highly susceptible to subjects’ physical activity levels because physical activity alters energy metabolism, which inevitably modulates the cardiorespiratory system and thereby changes the sympatho-vagal balance, regardless of stressors. Thus, researchers must simultaneously quantify the effect of physical activity on HRV to reliably assess sympatho-vagal balance under free-moving conditions. In the present study, dynamic body acceleration (DBA), which was developed in the field of animal ecology as a quantitative proxy for activity-specific energy expenditure, was used as a factor to correct for physical activity when evaluating HRV in freely moving subjects. Body acceleration and heart inter-beat intervals were simultaneously measured in cattle and sheep, and the vectorial DBA and HRV parameters were evaluated at 5-min intervals. Next, the effects of DBA on the HRV parameters were statistically analyzed. The heart rate (HR) and most of the HRV parameters were affected by DBA in both animal species, and the inclusion of the effect of DBA in the HRV analysis greatly influenced the frequency domain and nonlinear HRV parameters. By removing the effect of physical activity quantified using DBA, we could fairly compare the stress levels of animals with different physical activity levels under different management conditions. Moreover, we analyzed and compared the HRV parameters before and after correcting for the mean HR, with and without inclusion of DBA. The results were somewhat unexpected, as the effect of DBA was a highly significant source of HRV also in parameters corrected for mean HR. In conclusion, the inclusion of DBA as a physical activity index is a simple and useful method for correcting the activity-specific component of HRV under free-moving conditions.

Highlights

Heart rate variability (HRV) is an effective indicator of the activities of the autonomic nervous system and is widely used to assess the autonomic response to various internal and external factors (Acharya et al, 2006; von Borell et al, 2007; Billman, 2011)
Most of the values largely varied between animal species and even among individual animals, the arithmetic means of VeDBA, mean heart rate (HR), low frequency band (LF)/high frequency band (HF), and the two recurrence quantification analysis (RQA) parameters were lower for animals under the housing conditions than for animals under the grazing conditions
Positive correlations with the mean HR, low frequency band to HF (LF/HF), standard deviation 2 (SD2)/standard deviation 1 (SD1), and the two RQA parameters and negative correlations with the other parameters were observed in both animal species, indicating that the physical activity quantified by VeDBA affected the mean HR and the HRV parameters in a manner similar to a stressor

Summary

Introduction

Heart rate variability (HRV) is an effective indicator of the activities of the autonomic nervous system (i.e., the balance between sympathetic and vagal activity) and is widely used to assess the autonomic response to various internal and external factors (Acharya et al, 2006; von Borell et al, 2007; Billman, 2011). HRV is simultaneously affected by several interdependent physiological and environmental factors (Fatisson et al, 2016) because the sinus node acts as the final summing element of stimuli from the sympathetic and vagal nerves, and their relationship is reflected in the actual heart inter-beat intervals (Voss et al, 2009). HRV is strongly influenced by the change in average heart rate (HR) due to the simple mathematical problem of the inverse non-linear relationship between HR and inter-beat intervals (Sacha and Pluta, 2008; Billman, 2013a). There is a strong need to assess HRV under free-moving conditions in 24-h health monitoring contexts or in several HRV studies, such as psychophysiological studies

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