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Research field: Wearable Computing Systems and Machine Learning Algorithms for Applications in Sports and Medical Engineering

The researchers in the computer science in sports (a.k.a. Digital Sports) group at the Pattern Recognition Lab conduct theoretical and applied research for wearable computing systems and machine learning algorithms for engineering applications at the intersection of sports and health care. Our motivation is generating a positive impact on human wellbeing, be it through increasing performance, maintaining health, improving rehabilitation, or monitoring disease.

These are the research interests of the Digital Sports Group:

  • Machine learning in sports and medical engineering

    • Data mining and analysis of sports and medical data
    • Modeling and simulation of processes in sports
    • Biomedical and motion signal analysis
    • Pattern recognition algorithms for wearable and embedded systems
    • Applications include:

      • Injury prevention
      • Human movement analysis
      • Data mining of health related data

  • Wearable computing systems

    • Embedded systems integrated in clothes and equipment
    • Body-Area-Networking for near field communication
    • Signal processing, sensor and database fusion
    • Context-aware human activity classification
    • Automatic adaptation of algorithms to the individual
    • Applications include:

      • Physical activity measurement and motivation for increased health
      • Therapy support systems for musculoskeletal and neurodegenerative disorders
      • Ambient assisted living systems


The projects of the Digital Sports Group are listed on our homepage. One example project is miLife ("a wearable computing platform for applications in team sports and health care", in cooperation with adidas AG, Astrum IT GmbH, and the University Hospital Erlangen)

Digital Sports Group: Website & Projects



Supervised Theses

Curriculum Vitae