Nonlinear analysis of heart rate variability signals in meditative state: a review and perspective

Abstract

Introduction In recent times, an upsurge in the investigation related to the effects of meditation in reconditioning various cardiovascular and psychological disorders is seen. In majority of these studies, heart rate variability (HRV) signal is used, probably for its ease of acquisition and low cost. Although understanding the dynamical complexity of HRV is not an easy task, the advances in nonlinear analysis has significantly helped in analyzing the impact of meditation of heart regulations. In this review, we intend to present the various nonlinear approaches, scientific findings and their limitations to develop deeper insights to carry out further research on this topic. Results Literature have shown that research focus on nonlinear domain is mainly concentrated on assessing predictability, fractality, and entropy-based dynamical complexity of HRV signal. Although there were some conflicting results, most of the studies observed a reduced dynamical complexity, reduced fractal dimension, and decimated long-range correlation behavior during meditation. However, techniques, such as multiscale entropy (MSE) and multifractal analysis (MFA) of HRV can be more effective in analyzing non-stationary HRV signal, which were hardly used in the existing research works on meditation. Conclusions After going through the literature, it is realized that there is a requirement of a more rigorous research to get consistent and new findings about the changes in HRV dynamics due to the practice of meditation. The lack of adequate standard open access database is a concern in drawing statistically reliable results. Albeit, data augmentation technique is an alternative option to deal with this problem, data from adequate number of subjects can be more effective. Multiscale entropy analysis is scantily employed in studying the effect of meditation, which probably need more attention along with multifractal analysis. Methods Scientific databases, namely PubMed, Google Scholar, Web of Science, Scopus were searched to obtain the literature on “HRV analysis during meditation by nonlinear methods”. Following an exclusion criteria, 26 articles were selected to carry out this scientific analysis.

Heart–brain Rhythmic Synchronization during Meditation: A Nonlinear Signal Analysis

“…[ 2 ] Furthermore, meditation practice may have a significant effect on the autonomic nervous system. [ 3 ] Among all meditation practices known throughout the world, heartfulness meditation (HM) has a unique feature of “ Pranahuti or yogic transmission” to access the deeper levels of meditation. [ 4 ] It is a guided form of meditation where subtle energy is transmitted to the aspirant from the trainer.…”

Recognition of biosignals with nonlinear properties by approximate entropy parameters

“…They investigate the applicability of entropy in-dicators for the analysis of heart rate variability (HRV) [4,5], and also propose solutions to practical problems. These include detection of cardiac arrhythmias (atrial fibrillation) [6], detection of signs of chronic heart failure [6,7] recognition of meditative states [8], neonatal screening [9], identification of autonomic disorders of the cardiovascular system [10], assessment of the level of functioning of the autonomic nervous system by HRV [11]. In these publications, along with the discussion of the effectiveness of recognizing various states of an organism by biological time series, it is pointed out that the results obtained are highly dependent on the size of the analyzed data sample.…”