Hogeschool van Amsterdam

Playful Data-driven Active Urban Living (PAUL)


In big cities, people’s health is worse and their life expectancy shorter than in rural environments. This is partly due to lower physical activity of the inhabitants. In this project, we aim to gain a greater understanding of how the physical activity of city dwellers can be increased by using personalised app technology.

paul project

To date, existing health and exercise apps lack a scientific basis. Different apps use different ways of encouraging people to be physically active, such as instructional feedback on physical activity, motivational messages or games. Whether a particular way of motivating works is very personal. This means that an effective health app should be tailored to current activity level, health, personality and environmental factors, for example. However, it is still unclear how to find the best balance for each individual.

Video in Dutch

The aim of this project is to gather knowledge about personalizing app technology and developing an exercise app with different styles of feedback where the best possible match between app and user is used. The app will be used to collect data about the physical activity and the location of the user, which involves the collection of very large data sets (big data). We will use data mining techniques to deduce which app works best for different types of users. We will then give everyone their optimal app, and measure whether physical activity levels increase further. Based on the data, we can determine the effect of different types of exercise apps, and what app is most suitable for a particular person.



Project team

Project manager: Marije Deutekom (AUAS)
Team members: Ben Kröse, Joey van der Bie, Monique Schaule-Jullens, Nicky Nibbeling, Marije Deutekom (all AUAS), Monique Simons (Utrecht University) Prof. Dr. Victor Zuniga Dourado (UNIFESP, Sao Paolo)

Gepubliceerd door  Kenniscentrum Bewegen, Sport en Voeding 4 december 2017