Project Overview

Adherence to physiotherapy programs remains a critical challenge in healthcare. Despite prescribed exercises, many patients struggle to stay consistent over time and have slower recovery with suboptimal outcomes. This project explores how digital tools can support patients throughout their rehabilitation journey, with a focus on increasing engagement, consistency, and awareness of progress.

Physio – Fit is designed as a system that helps patients stay connected to their therapy beyond clinical sessions, supporting both physical recovery and behavioral change.

Methodology

The project is based on a combination of desk research and qualitative user research, aimed at understanding the reasons behind low adherence to physiotherapy programs. Research included:

• Analysis of scientific literature on rehabilitation and patient compliance;
• Interviews with physiotherapists;
• Observation of therapy sessions to understand real interactions.

Key insights revealed that it’s not simply a matter of motivation, but a combination of structural and psychological factors as limited understanding of progress and outcomes, lack of continuous support outside clinical sessions and difficulty maintaining routines over time. There’s a critical gap between clinical guidance and at-home execution, where patients often feel unsupported, and disconnected from their progress.

Concept Vision

No more Passive Compliance.

Physio-Fit is conceived as a therapy companion that:

• supports patients in understanding their progress;
• reinforces consistency through feedback and structure;
• bridges the gap between therapist and patient over time.

The concept combines progress visibility, guidance, and adaptive support, helping patients feel more in control of their recovery process, and shifts rehabilitation to an active and informed experience.

Designing an Experience

Central feature of Physio – Fit is the progress visualization, which makes improvements tangible over time and helps patients stay motivated. The system connects clinical input with everyday practice, ensuring that patients are not left alone in managing their therapy.

Key elements include:

• Personalized exercise plan defined by the therapist;
• Session tracking and reminders to support consistency;
• AI-supported suggestions to improve exercise execution;
• Walking-based exercises adapted to individual conditions;
• A real-time progression system, using with periodic clinical evaluation.

Learning Outcomes

Through this project, the student faces a challenge of working with more intangible dynamics such as motivation, perception of progress, and long-term engagement. A key shift came from understanding that in rehabilitation, improvement is often too gradual, and that the gap between actual and perceived progress directly affects adherence. This required learning how to translate something abstract into a tangible experience that could support users over time.

The process also challenged the student to work with a context where design does not operate in isolation, but intersects with clinical practices, routines, and constraints, and shape continuity — something that can realistically fit into everyday life without constant external support.