The geometry of synchronisation: Quantifying the coupling direction of physiological signals within and between individuals using inter-system recurrence networks.

The measurement of physiological signals using wearable sensors (heart rate, electrodermal activity, skin temperature) as well as motor activity, has become a reliable, nonintrusive and affordable method for monitoring e.g. general arousal and physical activity. In a clinical context, such measurements may provide a useful tool in the care of patients who are unable to verbally report on their current emotional or psychological state. In the present study we analyse multivariate physiological time series that were simultaneously recorded in dyads of caregivers and youth with severe mental disability in residential care. We investigate whether synchronization between physiological signals can be used to predict incidents that occur during the day, which often concern some form of aggression towards objects, self, or others. So-called Inter-system Recurrence Networks (ISRN, an extension of Cross Recurrence Quantification Analysis) can be used to determine whether a coupling direction exists between the physiological signals of caregiver and client networks. This gives insight in leading, following or bi-directional interactions of physiological signals, within and between dyad members. Such synchronization measures may serve as early warning signals of incidents and could serve as indicators for interventions to prevent incidents (e.g. take a break, disengage, change of context). We compare our results to ISRN based on simulations of delay-coupled dynamic system models.