Linguistic and emotional feedback for self-tracking physical activity

• Self-track the physical activity in order to monitor physical and mental disorders.
• Transparent and interpretable human activity model.
• Data acquisition by means of current smartphones placed wherever the user wants.
• An avatar communicates results in an emotional way according to the user needs.
• Experimentation presented to show the potential and applicability of the tool.

The level of physical activity is one of the most important parameters to monitor the evolution of some physical and mental disorders, e.g., obesity or depression. Its continuous monitoring provides an objective and quantitative measurement tool to be applied by therapists when developing patient-specific treatments. Most of existing activity recognition systems have been developed using multiple accelerometers strapped to the subject’s extremities. In this paper, we design an interpretable and transparent model able to describe the basic physical activity and the energy requirements of a person, by capturing the accelerations of its smartphone placed wherever he/she wants. In addition, the use of virtual agents that interact and communicate relevant information in an emotional way, increases the effectiveness and acceptance of the Human Computer Interfaces. Thus, we develop a computational application that combines activity recognition techniques with affective computing ones. We include first experimental results that demonstrate the potential and applicability of this tool.