Wavelet coherence reveals entrainment of heart rate variability among people involved in group activities

Abstract

The study of group dynamics is of primary importance in psychology and medicine because group dynamics affects the state of each member in a group. We study the RR interval time series, a heart rate measure, for a group of individuals involved in Kundalini meditation sessions. We analyze individual signals and study the wavelet coherence among the heart rate variability of different individuals. For specific activities, we found a high degree of coherence among all the people in the group. We also propose a novel method to detect temporally varying connections among the individuals based on the coherence of their heart rate.

A Bayesian model of heart rate to reveal real-time physiological information

“…This signal is collected off-line via Bluetooth using the Polar Team 2 proprietary software on a central server that can be accessed from a personal computer via IEEE 802.11. The data collected can be visualized and analyzed on our Healthware website [11], where it is possible to analyze the available data with several time-domain [1] and frequency domain [6] data analysis tools optimized for the analysis of this kind of signal. The website is publicly available; users can upload their own data collected through a heart rate sensor, and analyze it with the available tools.…”

“…Motivated by this causal connection between the ANS and heart rate, a vast literature has focused on modeling heart rate variability (HRV), i.e., the cyclic and acyclic variations in the instantaneous heart rate (IHR), see e.g., [2]- [6]. The IHR is calculated each time a pulse is detected; it is inversely proportional to the time interval between two pulses.…”

“…In previous work [6], we have exploited the wavelet trans formation to study the heart rate signal in the time-frequency domain. Using wavelet coherence [10], we were able to detect the presence of entrainment among people that are performing certain activities in unison.…”

Towards a real-time application to reveal entrainment among people

“…Once this huge amount of data is available, there arises the challenge to process it and extract relevant information. Towards this goal, in [6] we proposed an approach to measure the entrainment in a group of people using physiological signals. More specifically, we collected heart-rate data from a group of practitioners performing Kundalini Yoga meditation [7].…”

“…Exploiting wavelet coherence analysis, in [6] we proposed a method to reveal entrainment among people as a form of coherence of the spectral components of the instantaneous heart-rate signal of the individuals in the group. The drawback of the approach in [6] is the fact that it requires the whole dataset to calculate such coherence, revealing the entrainment only a posteriori, after the meditation session is concluded and the data has been fully processed.…”