Self-Quantification Systems to Support Physical Activity: From Theory to Implementation Principles
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Updated: Nov 25, 2025

Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity
Published on: March 7, 2019
Paul Dulaud1, Ines Di Loreto1, Denis Mottet2
1Tech-CICO (Technologies for Cooperation, Interaction, and Knowledge, in Collectives), Université de Technologie de Troyes, 12 Rue Marie Curie, 10000 Troyes, France.
Abstract:
Since the emergence of the quantified self movement, users aim at health behavior change, but only those who are sufficiently motivated and competent with the tools will succeed. Our literature review shows that theoretical models for quantified self exist but they are too abstract to guide the design of effective user support systems. Here, we propose principles linking theory and implementation to arrive at a hierarchical model for an adaptable and personalized self-quantification system for physical activity support. We show that such a modeling approach should include a multi-factors user model (activity, context, personality, motivation), a hierarchy of multiple time scales (week, day, hour), and a multi-criteria decision analysis (user activity preference, user measured activity, external parameters). This theoretical groundwork, which should facilitate the design of more effective solutions, has now to be validated by further empirical research.
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