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Pocket-based physiotherapist – Therapeutic AI-based training for the office and for rehabilitation at home - Civic Innovation Platform

Pocket-based physiotherapist

Therapeutic AI-based training for the office and for rehabilitation at home

Home and workplace physiotherapy training with real-time feedback on people’s execution of the movements – this is the idea behind the pocket-based physiotherapist. The Saxony Wrestling Association e.V., the company eCovery GmbH, the Centre for the Study of the Musculoskeletal System (ZESBO) and the Management School of the University of Kassel (KIMS-EAO) intend to jointly develop an application with which existing training therapy concepts can be improved.

Why are you a strong team?

We bring a variety of perspectives towards one common issue: maintaining employee health. We collate our experience in sensor technology, data science, industrial psychology, biomechanics and competitive sports and also operate at two different locations (Leipzig and Kassel) so that we can account for regional differences. There are no simple solutions for complex issues, which is why pooling our skills is a key factor to our success.

Explain your idea in three sentences.

We offer a physiotherapist for the hip pocket. A smart guide for physical therapy in a home office or anywhere else. Our medically sound app is intended to feature sensor technology and AI to help workers and patients contribute to recovering or maintaining their health themselves at home. With integrated AI, the app will keep learning from the training done by thousands of participants, delivering better recommendations and results to all users.

What makes your idea special?

We combine the foundations of a medical product (eCovery therapy app) with motion sensors, a machine learning approach and knowledge from the field of industrial psychology. The result is an app that provides sound guidance as well as smart direction and motivation (while constantly improving with training for training). We train the app in laboratory conditions with athletes and non-athletes, and then send it to people’s home living rooms. This attention to detail is unparalleled so far.

What are the next steps?

We are now taking the first steps for realising the pilot sketch. Athletes and non-athletes will train using motion sensors to teach the AI, while experts in the motion laboratory will assess the quality that each exercise is done with, helping sharpen the ideal vision for the movements. In parallel, we will lay the psychological foundations for an employee motivation model so that we are ready for large-scale testing of the solution. AI is what we make it!

Contact the project team