Smartwatches for Sport Applications


In this project we - a group of 13 students (electrical engineering) - investigate the usage of so-called smartwatches for sport applications. Our general goal is to get accurate motion information out of the data we can collect through smartwatches. Most smartwatches these days have all kinds of sensors, but especially interesting for our motion analysis are the gyroscopes and accelerometers. With this data we hope to capture how you move and then for example recall what you did or how well you’ve been doing. Every sport needs a different approach, so we’ve split up in teams to optimise what we know best and bring all of our knowledge into the analysis.

Participating Students

  • Alexander Weber
  • Dawyd Klimaschewski
  • Ruben Fiedler
  • Julian Jebe
  • Johannes Hoffmann
  • Daniel Beus
  • Fabian Bauer
  • Jannek Winter
  • Tim Rocholl
  • Michelle Djomo Njamen
  • Solveig Baschin
  • Kristina Apelt
  • Michel Boldt


  • Marco Gimm
  • Bastian Kaulen
  • Gerhard Schmidt




This part of the project is examining swimming sport.

In our group we are analyzing different signal patterns recorded by a multiple of sensors from a smartwatch while swimming the four official swimming styles defined by FINA (abbreviates Fédération Internationale de Natation):

  • breaststroke,
  • front crawl,
  • backstroke, and
  • butterfly.

The final goal is to develop a smartwatch application which contains an algorithm that is capable of logging the swim activity and determining the swimming style trough the help of analyzing e.g. acceleration patterns. The combination of multiple sensors of the smartwatch helps the algorithm to make a better decision which stroke one is swimming. It can help analyzing the training by give an exact logging on which styles, times and stroke count the swimmer used and can give long term feedback on how the swimmer is improving.

Team members
  • Solveig Baschin
  • Kristina Apelt
  • Michelle Djomo Njamen
  • Michel Boldt
Example Measurements



Prof. Dr.-Ing. Gerhard Schmidt


Christian-Albrechts-Universität zu Kiel
Faculty of Engineering
Institute for Electrical Engineering and Information Engineering
Digital Signal Processing and System Theory

Kaiserstr. 2
24143 Kiel, Germany

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