Sensors (Dec 2021)

Integrated Pedal System for Data Driven Rehabilitation

  • Alessandro Schaer,
  • Oskar Helander,
  • Francesco Buffa,
  • Alexis Müller,
  • Kevin Schneider,
  • Henrik Maurenbrecher,
  • Barna Becsek,
  • George Chatzipirpiridis,
  • Olgac Ergeneman,
  • Salvador Pané,
  • Bradley J. Nelson,
  • Nina Schaffert

Journal volume & issue
Vol. 21, no. 8115
p. 8115


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We present a system capable of providing visual feedback for ergometer training, allowing detailed analysis and gamification. The presented solution can easily upgrade any existing ergometer device. The system consists of a set of pedals with embedded sensors, readout electronics and wireless communication modules and a tablet device for interaction with the users, which can be mounted on any ergometer, transforming it into a full analytical assessment tool with interactive training capabilities. The methods to capture the forces and moments applied to the pedal, as well as the pedal’s angular position, were validated using reference sensors and high-speed video capture systems. The mean-absolute error (MAE) for load is found to be 18.82 N, 25.35 N, 0.153 Nm for Fx, Fz and Mx respectively and the MAE for the pedal angle is 13.2°. A fully gamified experience of ergometer training has been demonstrated with the presented system to enhance the rehabilitation experience with audio visual feedback, based on measured cycling parameters.