2026-05-19 ラトガース大学
＜関連情報＞
- https://www.rutgers.edu/news/tracking-tiny-facial-movements-could-offer-new-way-measure-pain
- https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2026.1702124/full
圧迫痛を感じている際の、ますます不規則になる心拍変動の指標としての顔面の微細な動き Facial micro-movements as a proxy of increasingly erratic heart rate variability while experiencing pressure pain
Elizabeth B. Torres,Mona Elsayed
Frontiers in Neuroscience Published:01 April 2026
DOI:https://doi.org/10.3389/fnins.2026.1702124
Abstract
Introduction:
The sensation of pain varies from person to person. These patterns of individual variation are difficult to capture using coarse subjective self-reports. However, they are important when prescribing therapies and tailoring them to each person’s own sensations. Pain can be experienced differently by the same person and can fluctuate based on context; yet, most analyses treat the problem with a one-size-fits-all model.
Methods:
In this work, we introduce a series of assays to assess pressure pain across tasks with different motoric and cognitive demands, in relation to a 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, such as inserting a grooved key into a matching keyhole. We adopt a standardized data type called micro-movement spikes (MMS) to characterize the biorhythmic activities of facial micro-expressions and the micro-fluctuations in the heart’s inter-beat interval timings.
Results:
Using the MMS peaks, we find that the continuous Gamma family of probability distribution functions best fits the frequency histograms of both the facial and heart data. Furthermore, 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. We find that as the heart IBI becomes more erratic (noisier and more random), the facial ophthalmic region also increases in noise and randomness, with higher linear correlation for tasks requiring haptic feedback (R2 0.84) and lower correlation for tasks requiring greater cognitive and memory loads (R2 0.77).
Conclusion:
Increases in transfer entropy show that recent past activity (~167 ms back) of the heart IBI and facial data combined lower the uncertainty in predicting the present ophthalmic facial activity, suggesting that this facial region may serve as a proxy for the increasingly dysregulated heart. These results have implications for the detection and monitoring of pressure pain.
