Development of a Unified Cardiovascular-Pupillary Model for Interpreting Pupil Size Variability as an Autonomic Marker.

IF 2.9 Q3 ENGINEERING, BIOMEDICAL
Biomedical Engineering and Computational Biology Pub Date : 2026-06-24 eCollection Date: 2026-01-01 DOI:10.1177/11795972261463516
Kevin Hung, Gary Man-Tat Man, Daniel Hung-Kay Chow
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Abstract

Background: Pupil size variability (PSV) has emerged as a potential non-contact indicator of autonomic nervous system (ANS) function; however, its physiological origins remain unclear. This study aims to develop a computational model to investigate the physiological foundations of PSV and assess how frequency-domain indices reflect cardiovascular autonomic balance. Methods: We integrated a well-established cardiovascular regulation model with a biomechanical pupillary muscle plant. The model simulates PSV alongside heart rate variability (HRV) by transmitting respiratory and baroreflex inputs through an indirect neural pathway to the pupillary muscles. Frequency-domain analyses were conducted to compare simulated PSV and HRV across different autonomic states. Results: Simulations suggest that PSV arises from respiratory and baroreceptor inputs, with its classical range-nonlinearity (RNL) property emerging naturally from iris biomechanics. The model reproduces key physiological behaviors, including inspiration-linked dilation and parasympathetic modulation. Frequency-domain analyses reveal low- and high-frequency components in PSV that are similar to those found in HRV. However, the magnitudes of these PSV components depend heavily on the underlying autonomic state and the mean pupil size. Conclusion: These findings provide a mechanistic framework for interpreting PSV as a cardiovascular autonomic biomarker. This ultimately supports the development of non-invasive, wearable, and eye-based ANS monitoring systems.

建立统一的心血管-瞳孔模型,将瞳孔大小变异性解释为自主神经标记。
背景:瞳孔大小变异性(PSV)已成为自主神经系统(ANS)功能的潜在非接触指标;然而,其生理起源仍不清楚。本研究旨在建立一个计算模型来研究PSV的生理基础,并评估频域指标如何反映心血管自主神经平衡。方法:将已建立的心血管调节模型与生物力学瞳孔肌装置相结合。该模型通过间接神经通路向瞳孔肌传递呼吸和压力反射输入,模拟PSV和心率变异性(HRV)。频域分析比较了不同自主状态下的模拟PSV和HRV。结果:模拟表明,PSV由呼吸和压力感受器输入产生,其经典的范围非线性(RNL)特性自然地从虹膜生物力学中产生。该模型再现了关键的生理行为,包括吸气相关的扩张和副交感神经调节。频域分析显示PSV的低频和高频成分与HRV相似。然而,这些PSV成分的大小在很大程度上取决于潜在的自主神经状态和平均瞳孔大小。结论:这些发现为解释PSV作为心血管自主生物标志物提供了一个机制框架。这最终支持了非侵入式、可穿戴式和基于眼睛的ANS监控系统的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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