Scalable Pervasive Health Environments

Principal Investigators

Prof. Dr. rer. nat. Rainer Malaka, Universität Bremen (Homepage)
Prof. Dr.-Ing. Marc Herrlich, TU Kaiserslautern (Homepage)

The project will focus on pervasive environments for health that are scalable across multiple users, multiple devices, and are designed for long-term use. Users will be able to employ exercise games (Exergames) to the benefit of their health using a variety of different devices and sensors available at their home, including existing game-related tracking devices, e.g. the Kinect, but also smartwatches, fitness trackers, or other sensors in the smart environment. We will investigate the potential of motivating interfaces that allow for long-term user engagement within these environments while adapting to user-specific needs and preferences. We focus on playful interactive interfaces within pervasive environments and examine methods to build them in a scalable way that incorporates existing non-pervasive Exergames and off-the-shelf games that can be turned into pervasive games for health. The second focus area of this project is the use of augmented and virtual reality environments to facilitate scalable development and evaluation of pervasive health environments in complex multi-device scenarios. This includes the application of machine learning (ML) techniques for data-driven long-term evaluation and prediction. This will enable users to play games for health adapted to their specific preferences and needs, utilizing the devices and wearables in their homes in a pervasive and scalable way.

Effects of PCG on Creativity in Playful City-Building Environments in VR

Volkmar, G., Alexandrovsky, D., Eilks, A.E., Queck, D., Herrlich, M. and Malaka, R.
Assessing the Impact of Procedural Content Generation on Creativity in VR City-Building Games

  1. Volkmar Georg, Dmitry Alexandrovsky, Asmus Eike Eilks, Dirk Queck, Marc Herrlich, and Rainer Malaka. 2022. Effects of PCG on Creativity in Playful City-Building Environments in VR using Filter Response Analysis. Proceedings of the ACM on Human-Computer Interaction 6, no. CHI PLAY (2022): 1-20.