Interpersonal Coordination Through Granger Causality Applied to AR Processes Modeling the Time Evolution of Low-Frequency Powers of RR Intervals

In this paper, interpersonal coordination is studied by analyzing physiological synchronization between individuals. To this end, a four-phase protocol is proposed to collect biosignals from the participants in each dyad. Then, the time evolution of the low-frequency (LF) power of the heart rate variability process for each participant is deduced. Finally, an approach based on a bivariate autoregressive model and Granger causality is proposed to determine whether a dependency exists between the biosignals. The approach is first applied to synthetic data and then to real data. This method has the advantage of providing explicit modeling of the dependency, which can help physiologists achieve better interpretation