Complexity Analysis of Skin Nerve Activity for Quantitative Assessment of Acute Sympathetic Nervous System Activation

Skin nerve activity (SKNA), extracted from electrocardiograms, is a noninvasive surrogate of sympathetic nervous system (SNS) activity. We evaluated whether complexity-based metrics derived from integrated SKNA (iSKNA; 500–1000 Hz) and time-varying SKNA (TVSKNA; 160–1140 Hz) discriminate SNS activation in experimental (n = 23) and clinical dental datasets (n = 49). Experimental tasks included the Valsalva maneuver and thermal grill stimulation; clinical recordings involved cold testing, with exploratory subgroup analyses based on anxiety status. Pain intensity was assessed using a visual analog scale (VAS); clinically significant pain (CSP+) was defined as a VAS score ≥ 4. Approximate entropy, sample entropy, Hjorth mobility and complexity, Katz fractal dimension, and standard deviation were computed. In the experimental dataset, the Valsalva maneuver produced large-to-huge effects (Cohen’s d = 1.93–3.46, p < 0.001). Thermal grill tasks showed moderate-to-large effects for adjacent pain levels (|d| = 0.63–0.71). ROC analysis showed strong discrimination for baseline vs. pain (AUC 0.80–0.99) but limited separation between adjacent pain levels (AUC 0.56–0.64). In the clinical dataset, discrimination was strongest for no pain vs. CSP+ (|d| = 0.86–1.17), with higher AUC in severe-anxiety participants (0.81–0.96) than non-severe (0.64–0.75). Complexity measures generally decreased during SNS activation, complementing amplitude-based changes. These findings support combined magnitude- and complexity-based descriptors for characterizing short-term sympathetic activation.