Short-timescale heart-rate fluctuation and acoustic stability show structured coupling at register transitions during singing

Abstract

Heart rate (HR) is widely used to index physiological activation during singing and music performance, yet condition-level mean HR provides limited insight into how physiological regulation unfolds during vocal task execution. This exploratory study examined whether short-timescale changes in HR and acoustic stability form a structured coupling pattern at vocal register transitions, and whether that structure is shared across singers or varies across individuals and task contexts. Twenty-five trained singers completed structured vocal tasks under low-, moderate-, and high-arousal conditions. Analyses focused on Low→ Middle and Middle→ High register-transition events. Short-timescale HR change was represented by the source-to-target difference in signed maximal short-timescale HR slope (Δs), whereas acoustic change was represented by the source-to-target difference in the composite acoustic-stability score (ΔA). Across 150 transition events, 72 were classified as aligned, 77 as opposed, and 1 as a tie. The aligned-minus-opposed proportion difference was −0.034, with a participant-cluster bootstrap 95% confidence interval of [−0.230, 0.160], providing no evidence for one dominant coupling direction. At the same time, the continuous association between Δs and ΔA was weakly negative, Pearson's r = −0.180, with a participant-cluster bootstrap 95% confidence interval of [−0.317, −0.040]. Individual profiles were heterogeneous, with more than half of the singers showing mixed rather than consistently aligned or opposed coupling. These findings indicate that short-timescale HR fluctuation and acoustic stability are modestly but observably structured at register transitions, without supporting a single dominant group-level coupling direction. Physiological–acoustic coupling in singing is therefore better understood as task- and person-sensitive rather than as a uniform response or fixed physiological target. This event-based framework provides an empirical basis for person-specific regulatory profiling, multimodal performance analysis, and future human-in-the-loop computational approaches to vocal assessment and feedback.