Personal Analytics and Digital Health

We investigate novel approaches for highly adpative persuasive technology related to health and well-being. Persuasion can, for instance, be realized in a playful way—as a serious game—or as a monitoring app. In our work we focus on activity recognition, user-modelling and methods to generate user- and context-adaptive recommendations. Our work in this area is interdisciplinary integrating the disciplines computer engineering, cognition science, ethics, electrical engineering, and health science.

Personal Analytics

Personal Analytics for health reasons, also known as Self-Monitoring, Health-Monitoring, Self-Tracking, or Quantified Self, is a new research topic with increasing relevance pushed by a wide-spread of smartphones and sensor-technologies for private use. The research topic implies the fields of pervasive computing, ubiquitous sensor networks, data analysis, and persuasive technology.

Publications

Health and Serious Games

A serious game is a specific type of game whose primary purpose goes beyond pure entertainment by teaching knowledge or training skills. Our group develops and evaluates serious game concepts and prototypes within different application areas with a focus on health care, physical and mental fitness. The track record of our group includes games like a health game prototype, which shall improve the self-management process of teenage patients with insulin-dependent diabetes as well as a serious game with tangible interfaces for cognitive training.

Publications

Contact

Jürgen Ziegler

Full Professor

Related publications

Using psychophysiological parameters to support users in setting effective activity goals

Sensor-based and tangible interaction with a TV community platform for seniors

Das Projekt PAnalytics – Selbstmonitoring für gesundes Altern

Health Recommender Systems for Mental Health Promotion

Integrating Behavior Change and Persuasive Design Theories into an Example Mobile Health Recommender System

Towards a User Integration Framework for Personal Health Decision Support and Recommender Systems

Mobile mood tracking: An investigation of concise and adaptive measurement instruments

Exploring chatbot user interfaces for mood measurement: A study of validity and user experience

Investigating mechanisms for user integration in the activity goal recommendation process by interface design

Rating-based preference elicitation for recommendation of stress intervention

More related publications »

Related projects

PAnalytics

Developing a holistic persuasive self-monitoring system to support healthy aging

Engage.NRW

Interaktive Lösungen für die Wirtschaft / Interactive solutions for business

GDI Ruhr

Tapping the full potentials of the games industry and incarnating these into an expertise-network

FoSIBLE

Developing a social-network platform for elderly people

Related developments

PAX

Stress resilience, a health recommender system for mental health promotion

PAX Mood Tracker

Mood Tracking: assessment quality vs. app quality

Merobrixx

A serious game for training mental rotation skills