Vitalflow
What?
Literature on personal informatics (PI) systems highlights the potential benefits of self-tracking for well-being. However, many existing systems limit these benefits, by imposing predefined goals on the users. This project contributes to a paradigm shift towards non- judgemental interfaces by developing a non-judgemental PI system for tracking and interacting with breathing data. This project, therefore, employs the data-enabled design process, focusing on exploration, rather than behavioral change. The chosen context of breathing tracking is explored through the design and deployment of technologies for measuring, visualizing and interacting with breathing data. A creative approach was taken in analysing the data, leading to insights on the preferred location and time of use, the usability of the system, and data physicalization. Additionally, concerns for these systems are argued for. Ultimately, this project bridges the gaps in PI literature and design practices by utilizing dynamic data physicalization and data-enabled design principles.
What did I contribute?
Rapid prototyping
Data visualization in Python
Conducting user research
Developed skills
Developing soft robotic actuators
Creative ways of performing data analysis
Presenting
What were my main takeaways?
I had the opportunity to develop a soft robotics actuator, which confirmed my growing interest in soft robotics.
The margins and errors that should be accounted for when developing and manufacturing moulds for soft robotics.
I have developed a strong visual language for my presentations, providing the opportunity to tell a more engaging and coherent story.