Combining Computer Vision, Artificial Intelligence and 3D Printing in Wheelchair Design Customization: The Kyklos 4.0 Approach


  • Yacine Rebahi Fraunhofer Fokus, Germany
  • Mahmoud Gharra Fraunhofer Fokus, Germany
  • Luca Rizzi European Research Centre for Design and Materials Technologies, Italy
  • Ilias Zournatzis TWI Hellas Astiki Mi Kerdoskopiki Etaireia, Greece



additive manufacturing, artificial intelligence, design customization, wheelchair, footrest, Kyklos 4.0, circular economy


In the current paper, we present our work towards developing a solution combining computer vision and AI to support footrest design customization in the wheelchair industry. Wheelchairs and postural systems are complex and often user centric in the design process. Those products require a wide range of adjustments to adapt to the various anthropometries and disabilities of patients. Most commercial products, dedicated to severe disability, also include a series of additional elements, designed to keep the patient in a comfortable but “fixed” position. Such systems do not allow to “fix and maintain” the position of patient foot, especially for patients who have no control over their lower limbs. For that reason, it becomes essential to supply wheelchairs with specific elements to hold patient's shoe in place. Commercial foot supports are typically developed on standard sizes and do not always cover the entire population. In addition, those designs are based on standard shoes, thus they do not lend themselves well to adapting to special shoes or orthopedic shoes.  Feet final position therefore becomes a key element in correct postural management. In this paper, we investigate the use of computer vision and AI to correctly define customization parameters of the footrest. The proposed design has been developed based on the specifications received from the Pro Medicare S.r.l[] orthopedic technicians. We present suitable algorithms, design principles and well defined components towards the implementation of our proof of concept. We also present the testing activities we have undertaken and the obtained performance results.


Received: 26 June 2023 | Revised: 20 July 2023 | Accepted: 31 July 2023


Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.


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How to Cite

Rebahi, Y., Gharra, M., Rizzi, L., & Zournatzis, I. (2023). Combining Computer Vision, Artificial Intelligence and 3D Printing in Wheelchair Design Customization: The Kyklos 4.0 Approach. Artificial Intelligence and Applications.



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