Powered Rehabilitation Tricycle with Intelligent Stimulation Capacity
To improve the health of people with limited mobility, researchers are developing an intelligent functional electrical stimulation system to be integrated into the GO-TRYKE rehabilitation tricycle.
Factsheet
- Schools involved School of Engineering and Computer Science
- Institute(s) Institute for Human Centered Engineering (HUCE)
- Research unit(s) HuCE / Reha Lab
- Funding organisation Innosuisse
- Duration (planned) 01.11.2021 - 01.05.2024
- Head of project Prof. Dr. Kenneth James Hunt
-
Project staff
Dr. Efe Anil Aksöz
Prof. Sebastian Tobler - Partner GBY SA
- Keywords Rehabilitation, functional electrical stimulation
Situation
In 2019, the company GBY AG launched the GO-TRYKE to help people with limited mobility to move more freely and improve their health in the process. The special feature of the GO-TRYKE tricycle is that the movement of the arms causes the legs to move asynchronously, which corresponds to a natural movement pattern. Now the company is working together with researchers from the Institute for Human Centered Engineering HuCE at Bern University of Applied Sciences BFH to expand the GO-TRYKE system with an intelligent functional electrical stimulation system (iFES). Exercise thanks to functional electrical stimulation has several clinically and scientifically proven benefits for general health: among other things, it trains the cardiovascular system, strengthens the muscles, increases bone density, and improves breathing.
Course of action
The project plans to combine the GO-TRYKE tricycle with a functional electrical stimulation system. The paralysed leg muscles are to be activated by current impulses so that they no longer just passively moved. The activation is achieved by electrodes on the skin. The system is designed to collect data from the arms and legs during movement. This includes, for example, strength, position, and speed of movement. This data is used to automatically adjust the stimulation to the user's effort. All data from the experiments are uploaded to a cloud server and the analysis is done via an app. In addition, non-contact sensors for speed and heart rate are integrated into the system for accurate outdoor measurements.
