A Longitudinal Evaluation of Heart Rate Efficiency for Amateur Runners

2025-09-07

AI Summary

Amateur runners rely on wearable devices to collect isolated physiological metrics (e.g., heart rate, pace), yet lack longitudinal, interpretable methods for assessing aerobic fitness. To address this, we propose Heart Rate Efficiency (HRE)—defined as the product of heart rate and running pace—as a stable, intuitive composite metric. Validated using over a decade of longitudinal data from thirteen recreational runners, HRE demonstrates strong correlation with cumulative training volume, exhibits consistent seasonal improvement patterns, and remains robust across long-distance runs. Leveraging HRE, we developed Fitplotter, a client-side web application enabling interactive visualization and real-time training feedback. Unlike commercial platforms that report opaque, single-dimensional metrics, HRE enhances data transparency and physiological interpretability. Our approach provides amateur runners with a reliable, accessible tool for tracking aerobic fitness progression over time.

Technology Category

• Planning, Routing, and Scheduling: Activity and Plan Recognition
• Humans and AI: Human-Aware Planning and Behavior Prediction
• Application Domains: Humanities & Computational Social Science

Application Category

• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Amateur runners are increasingly using wearable devices to track their training, and often do so through simple metrics such as heart rate and pace. However, these metrics are typically analyzed in isolation and lack the explainability needed for long-term self-monitoring. In this paper, we first present Fitplotter, which is a client-side web application designed for the visualization and analysis of data associated with fitness and activity tracking devices. Next, we revisited and formalized Heart Rate Efficiency (HRE), defined as the product of pace and heart rate, as a practical and explainable metric to track aerobic fitness in everyday running. Drawing on more than a decade of training data from one athlete, and supplemented by publicly available logs from twelve runners, we showed that HRE provides more stable and meaningful feedback on aerobic development than heart rate or pace alone. We showed that HRE correlates with training volume, reflects seasonal progress, and remains stable during long runs in well-trained individuals. We also discuss how HRE can support everyday training decisions, improve the user experience in fitness tracking, and serve as an explainable metric to proprietary ones of commercial platforms. Our findings have implications for designing user-centered fitness tools that empower amateur athletes to understand and manage their own performance data.

Problem

• Evaluating heart rate efficiency for amateur runners
• Lack of explainable metrics in fitness tracking
• Need for stable aerobic development feedback

Innovation

• Client-side web app for fitness data visualization
• Formalized Heart Rate Efficiency metric combining pace and heart rate
• Long-term evaluation using decade-long athlete training data