TeMoRett: XR and AI support motor function therapy in Rett syndrome

The TeMoRett project aims to develop technology-based motor rehabilitation for people with Rett syndrome. This rare genetic disorder predominantly affects girls and, in addition to the loss of spoken language, also leads to movement disorders of the hands. An interdisciplinary consortium was formed for the project.

Paul Chojecki is the overall project leader. In an interview with MEDICA-tradefair.com, the psychologist talks about the development in the TeMoRett project and how it is intended to help affected individuals.

Mr. Chojecki, what could rehabilitation with this system look like?

Paul Chojecki: The problem of the affected persons, mostly young girls, is the control of hand movements. In order to be able to start therapy as early as possible, the simplicity of the therapy and immediate rewards to promote motivation are important.

For the therapy, tasks are set to move the hands. The webcam of a laptop will recognize the position of the hands and thus the voluntary hand movements. In addition, the stress level based on facial expressions and physiological data will be recorded.

With this data, we can develop individual therapy programs with increasing difficulty. The game elements and rewards, which consist of media content, are projected onto the table at arm’s length.

What role do the technologies play?

Chojecki: Extended Reality (XR) and Artificial Intelligence (AI) are used, which are constantly evaluated and further developed in conjunction with the results of our project partners. Disciplines such as neuroscience (MPI) and pediatrics (Charité) as well as the Rett competencies of Georgetown University in Washington and Rett Syndrom Deutschland e. V. are involved.

Hand movements and physiological data are recorded contactless via a camera, as most patients are very sensitive to touch or worn devices. To recognize the difficulty of individual tasks, an algorithm will evaluate this data. Voluntary movements should be quickly recognized and reinforced by rewards. The therapy should be inexpensive to use and possible in families.

Is the technology comparable to that used for gesture control?

Chojecki: The technology builds on our preliminary work on gesture control but is more complex. Hand orientation and ergonomic aspects are significant, and recognition must be much more precise. One consequence of the disease is stereotypes such as repetitive 'hand washing' movements, which make recognition of voluntary hand movements difficult. Personalizable exercises should help develop voluntary hand movements and reduce stereotypes.

In the future, this technology could also be used to control nursing or therapy robotic systems, not just for Rett patients.

What are the benefits of this?

Chojecki: We want to promote training effects through rewards and gamification. Patients are not always at their best when therapists are available. The digital solution can be used at home. Here, many repetitions are possible, and the timing can be freely chosen.

Since the results are available digitally, the procedure can also be evaluated and used telemedically. Access to treatment providers, who are often found in large cities, is thus facilitated.

What role do families play?

Chojecki: The disease is often diagnosed within the first two years of life. Information about the therapy should be spread at pediatric centers and through our project partner, the Rett Syndrome Germany association. During the development phase, the wishes and requirements of children, families and treatment providers must be identified, and the technology must be continually adapted to their needs.