Look into your Heart -- Prototypes for a Speculative Design Exploration of Personal Heart Rate Visualization

TL;DR

The paper tackles the challenge of interpreting personal heart rate data by introducing five speculative visualization prototypes (circadian heatmaps, recurrence plots, PSD spectrograms, TSNE, and Poincaré plots) grounded in established visualization literature. It leverages physiologically-informed synthetic data generated by large language models to explore how these visualizations reveal multiscale temporal patterns and autonomic dynamics. Evaluation uses BeauVis and PreVis scales with surrogate personas to map design tensions between literacy, aesthetics, and comprehension. Findings show a strong link between comprehension and aesthetic appeal, with simpler formats remaining accessible across users while more complex visualizations require scaffolding; collectively, the work maps a speculative design space for patient-centered heart rate visualization that informs future empirical validation.

Abstract

Personal heart rate data from wearable devices contains rich information, yet current visualizations primarily focus on simple metrics, leaving complex temporal patterns largely unexplored. We present a speculative exploration of personal heart rate visualization possibilities through five prototype approaches derived from established visualization literature: pattern/variability heatmaps, recurrence plots, spectrograms, T-SNE, and Poincaré plots. Using physiologically-informed synthetic datasets generated through large language models, we systematically explore how different visualization strategies might reveal distinct aspects of heart rate patterns across temporal scales and analytical complexity. We evaluate these prototypes using established visualization assessment scales from multiple literacy perspectives, then conduct reflective analysis on both the evaluation and the design of the prototypes. Our iterative process reveals recurring design tensions in visualizing complex physiological data. This work offers a speculative map of the personal heart rate visualization design space, providing insights into making heart rate data more visually accessible and meaningful.

Figures (9)

• Figure 1: Heart Rate in BPM for a Week
• Figure 2: Heart Rate Variability through the Week
• Figure 3: Heart Rate Clock from Tuesday to Sunday
• Figure 4: Zoomed in Monday Heart Clock
• Figure 5: The Renaissance Recurrence Plot. Both the axes are time indices.