5th International ICST Conference on Body Area Networks

Research Article

Body Area Wireless Sensor Networks for the Analysis of Cycling Performance

  • @INPROCEEDINGS{10.1145/2221924.2221926,
        author={Raluca Marin-Perianu and Mihai Marin-Perianu and David Rouffet and Simon Taylor and Paul Havinga and Rezaul Begg and Marimuthu Palaniswami},
        title={Body Area Wireless Sensor Networks for the Analysis of Cycling Performance},
        proceedings={5th International ICST Conference on Body Area Networks},
        keywords={cycling sports body area networks wireless motion sensor networks inertial sensing online feedback},
  • Raluca Marin-Perianu
    Mihai Marin-Perianu
    David Rouffet
    Simon Taylor
    Paul Havinga
    Rezaul Begg
    Marimuthu Palaniswami
    Year: 2012
    Body Area Wireless Sensor Networks for the Analysis of Cycling Performance
    DOI: 10.1145/2221924.2221926
Raluca Marin-Perianu1,*, Mihai Marin-Perianu2, David Rouffet3, Simon Taylor3, Paul Havinga1, Rezaul Begg3, Marimuthu Palaniswami4
  • 1: Pervasive Systems Group, University of Twente
  • 2: Inertia Technology
  • 3: Institute of Sport Exercise and Active Living - School of Sport and Exercise Science - Victoria University
  • 4: University of Melbourne
*Contact email: raluca.marinperianu@utwente.nl


In high-performance cycling, there is a need for advanced technological means of assessing the cyclists’ performance during training and competition, and the risk of overuse injuries. Existing techniques rely on off-line, laboratory-based analysis, as well as on outfitting the bike with various sensors and transducers that give an estimate of the performance during training and racing. We propose a radically different approach, with the aim of determining the actual status of the cyclist’s body in real-time and real-life conditions. Our solution is based on body area wireless motion sensor nodes that can collaboratively process the sensory information and give immediate feedback to the cyclists. We study experimentally the accuracy of such a system with respect to the gold standard camera system. The biomechanics measures of interest are the knee and ankle angles of the cyclists, which give an indication of the correctness and efficiency of the cycling technique. The results obtained from a series of experiments with nine subjects show the accuracy of the motion sensor system compared with the reference given by the camera system. Furthermore, we analyse the wireless characteristics of our system, the energy expenditure and possible improvements.