FES / Functional Electrical Stimulation Bike Race



About the Team

In 2019, a group of scientists and students from Politecnico di Milano (POLIMI) began to work on the prototype of a Functional Electric Stimulation (FES) bike, to compete at CYBATHLON 2020. Since then, many researchers, students and pilots have been working to improve the device and the team's performance. The addition of new sensors to improve the feedback from the trike and the study of different stimulation strategies are two of the main novelties introduced by the POLIMI team to be competitive for CYBATHLON 2024. Moreover, a usability study was carried out to enhance user involvement in the optimisation of the prototype. The POLIMI team aims to increase awareness in society about assistive technologies and their use in daily life thanks to the spotlight offered by the CYBATHLON initiative.

About the Pilot

Andrea Gatti has been an integral part of our team since 2019, bringing with him not only exceptional determination and dedication but also a remarkable talent as a multifaceted athlete. His prowess on the table tennis court saw him clinch the 5th position at the Italian Table Tennis Championship, a testament to his commitment, skill, and competitive spirit. In 2020, Andrea's journey soared to new heights as he claimed the seventh position at CYBATHLON, underscoring his resilience and determination in the face of challenges. As he prepares to compete at CYBATHLON 2024, we couldn't be prouder to stand behind him, offering our unwavering support and enthusiasm.

About the Device

Our device is an FES-controlled recumbent trike, compatible with the CYBATHLON rules for the FES Bike Race. It consists of a passive three-wheel trike customized with a magnetic encoder, two sensorised pedals, and neuromuscular electrical stimulators (HASOMED GmbH). A crank-angle-based stimulation strategy is used to generate the cycling motion and a Proportional-Integrative controller modulates the stimulation intensity to keep a constant pedalling cadence. A symmetry controller is added to ensure a balanced and smooth pedalling movement. The control system runs on a Raspberry Pi 4. Up to 12 different muscle groups can be stimulated and transcutaneous Spinal Cord Stimulation can also be exploited. During the race, the pilot can adjust either the stimulation intensity or the target cadence using buttons. An Android application for setting training parameters and providing real-time feedback completes the system.

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