Temporal Cardiovascular Dynamics for Improved PPG-Based Heart Rate Estimation

• URL: http://arxiv.org/abs/2510.27297v1
• Date: Fri, 31 Oct 2025 09:12:14 GMT
• Title: Temporal Cardiovascular Dynamics for Improved PPG-Based Heart Rate Estimation
• Authors: Berken Utku Demirel, Christian Holz,
• Abstract summary: We study the non-linear chaotic behavior of heart rate through mutual information.<n>Our proposed approach handles the non-linear temporal complexity from a mathematical perspective.<n>Our results demonstrate a substantial improvement, up to 40%, of the proposed approach in estimating heart rate.
• Score: 35.715609556178165
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: The oscillations of the human heart rate are inherently complex and non-linear -- they are best described by mathematical chaos, and they present a challenge when applied to the practical domain of cardiovascular health monitoring in everyday life. In this work, we study the non-linear chaotic behavior of heart rate through mutual information and introduce a novel approach for enhancing heart rate estimation in real-life conditions. Our proposed approach not only explains and handles the non-linear temporal complexity from a mathematical perspective but also improves the deep learning solutions when combined with them. We validate our proposed method on four established datasets from real-life scenarios and compare its performance with existing algorithms thoroughly with extensive ablation experiments. Our results demonstrate a substantial improvement, up to 40\%, of the proposed approach in estimating heart rate compared to traditional methods and existing machine-learning techniques while reducing the reliance on multiple sensing modalities and eliminating the need for post-processing steps.

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