Published September 9, 2025 | Version 1.0

Facial Micro-Movements as a Proxy of Increasingly Erratic Heart Rate Variability While Experiencing Pressure Pain

  • 1. ROR icon Rutgers, The State University of New Jersey

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  • 1. ROR icon Rutgers, The State University of New Jersey

Description

Data sets from neurotypical participants acquired during resting (control) state and during pain state induced by a sustained pressure on the arm using a blood pressure cuff.

Abstract

The sensation of pain varies from person to person. These patterns of individual variations are difficult to capture using coarse subjective self-reports. However, they are important when prescribing therapies and tailoring them to the person’s own sensations. Pain can be experienced differently by the same person, and fluctuate differently depending on the context, yet most analyses treat the problem under a one-size-fits-all model. In this work, we introduce a series of assays to objectively assess pressure pain across tasks with different motoric and cognitive demands, in relation to resting state. In a cohort of healthy individuals, we examine pain-free vs. pain states at rest, during drawing with heavy cognitive demands, during pointing to a visual target, and during a grooved peg task like inserting a grooved key in a matching grooved keyhole. We recorded Face videos, electrocardiographic signals and adopt a standardized data type called the micro-movement spikes (MMS) to characterize the biorhythmic activities of the Face micro-expressions and of the micro-fluctuations in the heart’s inter beat interval timings. Using the MMS peaks, we find that the continuous Gamma family of probability distribution functions best fit the frequency histograms of both the Face and the heart data. Further, we find that the Gamma shape and scale parameters in both signals span a scaling power law whereby as the noise-to-signal ratio (Gamma scale parameter) increases, so does the randomness of the stochastic process (the Gamma shape decreases towards the memoryless exponential range). We find that as the heart IBI turns more erratic (noisier and more random) the facial ophthalmic region increases the noise and randomness too, with higher linear correlation for tasks requiring haptic feedback (R2 0.84) than for tasks requiring higher cognitive and memory loads (R2 0.77). Increases in transfer entropy shows that recent past activity (~167ms back) of the heart IBI and Face combined lower the uncertainty in the prediction of the present ophthalmic-Face activity, suggesting that this Face region may serve as a proxy of an increasingly dysregulated heart. These results bear implications for the detection and monitoring of pressure pain and heart dysregulated states.

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Additional details

Funding

Nancy Lurie Marks Family Foundation
Career Continuation Award

Dates

Submitted
2025-09-08
Data set for paper under review

Software

Programming language
MATLAB
Development Status
Active