On the picture on your left, you can see how the suit is and what is shown on the computer. On the picture on your right, you can see the smartwatch and the application we created.

In BIONIC, our work was focused on estimating fatigue from sensors by machine learning algorithms (which you can read more about in the papers [1] and [2] in the reference list below) and the development of coaching strategies for healthy lifestyle for the gamification application.

In this blog article, I would like to tell you a bit more about this gamification application we developed, which has the following components (to get a better idea, see video below):

• Overview of measured daily activity: users can get insights on their daily activities (step counts). The application (through an algorithm) can estimate the moments in which the user shows sedentary behavior (staying too much sitting) and the periods in which (s)he is doing some activity.
• Overview of subjective fatigue: every day, users will be asked, with a question in the app, how tired they feel that day. The answers to this question will be shown in a graph.
• Personalized exercise program: physiotherapy exercises advised to users in form of trainings and depending on which part of the body a user has the most issues (for instance, back, neck, or legs).
• Motivational support via virtual coach Bill and gamification elements: Proposing physiotherapy exercises according to the feedback received from the BIONIC system and the needs of the users. These exercises are given by a virtual coach, Bill, who guides, motivates, and supports users. The Gamification App has gamification features to prompt users to do the exercises proposed and to change their physical activity (when needed). These gamification features entail earning points through:
  • Challenges: a set of goals that the user can set up for him-/herself
  • Achievements: a set of tasks that the user can achieve whilst using the Gamification App

The Gamification App was also evaluated in clinical settings at Roessingh to investigate if this technology could be of added value. From this evaluation, we discovered that the application could really help patients to be more aware of their activity patterns and it could motivate them to change their activity behaviors and facilitate rehabilitation.

We are really proud of what we achieved in these years considering that we were able to develop a working application of which added value was seen. The project is now finished, but we will bring with us what we have learnt during these years and we hope to further develop and use the application for other purposes.