The intelligent knee support bandage dubbed as the "Anthrokinemat" is intended to help osteoarthritis patients in the near future with the proper adjustment of their everyday movements.
All relevant data regarding joints strain are collected and transferred to the patient's mobile phone. Sports scientists from the Karlsruhe Institute of Technology (KIT) have created the base technology for the development of the bandage. Partners include the University of Bremen, the bandage manufacturer Bauerfeind and the sensor technology company ITP. A prototype is now under development.
"In addition to weight and nutrition, the right amount of exercise plays an important role in the prevention and treatment of osteoarthritis," says sports orthopedic surgeon Professor Stefan Sell from the Institute of Sports and Sports Science (German acronym: IfSS) at the KIT. However, finding the right amount of exercise is not an easy task and only a few people and well-trained athletes are able to interpret the signals of their body correctly without professional support.
Therefore, the “Anthrokinemat” is equipped with numerous sensors and designed to sensitize osteoarthritis patients to possible damage through warning signals on their mobile phones before they exceed their joint stress limit. "Anyone suffering from arthrosis is best advised to refrain from intensive exercise every day for a certain period of time," advises Sell. Excessive strain, such as a hike lasting several hours, can cause stress in the damaged joints. The consequences of such overloading are often pain lasting for weeks.
Professor Thorsten Stein, head of the BioMotion Center at the IfSS, explains that the greatest challenge in the bandage’s development so far was the search for a suitable algorithm to quantify knee stress. "The sensors can only measure movement, not the load as such. In osteoarthritis, however, the joints must not be put under too much strain - and that's why we needed to be able to estimate the forces inside the knee as accurately as possible," Stein emphasized. Machine learning algorithms applied as artificial neural networks are used to solve this problem. An algorithm is trained with motion data: In the course of the training process, the algorithm automatically learns to estimate the forces in the knee associated with a movement. The research groups of Prof. Sell and Prof. Stein have already published parts of these research results in the journal Sensors.
Bernd J. Stetter, Steffen Ringhof, Frieder C. Krafft, Stefan Sell, Thorsten Stein: Estimation of Knee Joint Forces in Sport Movements Using Wearable Sensors and Machine Learning. Sensors, 2019. DOI: 10.3390/s19173690.