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 (<i>n</i> = 23) and clinical dental datasets (<i>n</i> = 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 <i>d</i> = 1.93-3.46, <i>p</i> < 0.001). Thermal grill tasks showed moderate-to-large effects for adjacent pain levels (|<i>d</i>| = 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+ (|<i>d</i>| = 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.