Point process Respiratory Sinus Arrhythmia analysis during deep tissue pain stimulation

We present an analysis of autonomic nervous system responses to deep tissue pain by using an instantaneous point process assessment of Heart Rate Variability (HRV) and Respiratory Sinus Arrhythmia (RSA). Ten subjects received pressure stimuli at 8 individually calibrated intensities (7 painful) over three separate runs. An inverse Gaussian point process framework modeled the R-R interval (RR) by defining a bivariate regression incorporating both past RRs and respiration values observed at the beats. Instantaneous indices of sympatho-vagal balance and RSA were estimated combining a maximum-likelihood algorithm with time-frequency analysis. The model was validated by Kolmogorov-Smirnov goodness-of-fit and independence tests. Results show that, in comparison to the resting period, all three pain runs elicited a significant decrease in RSA by over 21% (p=0.0547, 0.0234, 0.0547) indicating a reduced parasympathetic tone during pain, with RSA estimates negatively correlated with the calibrated stimulus intensity levels (slope = -0.4123, p=0.0633).