Self-Quantification Systems to Support Physical Activity: From Theory to Implementation Principles.

Area of Science:

• Health Informatics
• Behavioral Science
• Human-Computer Interaction

Background:

• The quantified self movement aims for health behavior change.
• Existing theoretical models for self-quantification are too abstract for practical application.
• Effective user support systems are needed to facilitate successful health behavior change.

Purpose of the Study:

• To propose principles linking theory and implementation for self-quantification systems.
• To develop a hierarchical model for adaptable and personalized physical activity support.
• To bridge the gap between abstract theory and practical design of user support systems.

Main Methods:

• Literature review of theoretical models for self-quantification.
• Development of a hierarchical model for a personalized self-quantification system.
• Inclusion of a multi-factors user model (activity, context, personality, motivation).
• Integration of a hierarchy of multiple time scales (week, day, hour).
• Application of multi-criteria decision analysis (user activity preference, user measured activity, external parameters).

Main Results:

• A theoretical framework for designing adaptable and personalized self-quantification systems.
• A hierarchical model incorporating user-specific data and temporal scales.
• A multi-criteria decision analysis approach for tailored physical activity support.

Conclusions:

• The proposed model provides a foundation for creating more effective self-quantification solutions.
• This approach facilitates the design of personalized user support for physical activity.
• Further empirical research is required to validate the theoretical groundwork.