Data Driven Medical muscle Training
At a glance
- Project leader: Prof. Dr. Rudolf Marcel Füchslin
- Deputy of project leader: Dr. Lukas Lichtensteiger
- Project team: Dr. Philipp Ackermann, David Graf, Prof. Dr. Juan-Mario Gruber
- Project status: completed
- Funding partner: Internal
- Project partner: Eidgenössische Technische Hochschule Zürich ETH / Exercise Physiology Lab
- Contact person: Rudolf Marcel Füchslin
Muscle loss is a concomitant of various diseases (cachexia) and
the usual aging process (sarcopenia). Limiting this reduction and,
ideally, even reversing it makes medical and economic sense. In
medicine, the metabolic function (in addition to the pure movement)
of the muscles is increasingly understood and recognized in their
therapeutic relevance; for chronic diseases, e.g. HIV or cancer has
been shown to help patients with higher muscle mass survive longer.
From the point of view of most older people as well as from an
economic perspective, it is desirable to make it possible to stay
as long as possible in one's own living space. Well-developed
muscles are a necessary prerequisite for this.
Strength training is an established measure against cachexia / sarcopenia. At present, such training is characterized by a few non-dynamic parameters (type of exercise, number of repetitions, force to be applied). Recent findings (from molecular physiology and exercise science) suggest that the success of strength training is influenced not only by these static parameters, but also by the way in which movements are performed. The Institute of Systems Biology (Prof. Dr. Ernst Hafen) and the Laboratory of Sports Physiology (Prof. Dr. Christina Spengler) of the ETH Zurich are investigating ways to better parameterize training through additional mechano-biological descriptors, to characterize their relevance for muscle building and as a consequence to make the trainings accessible to further personalization and optimization. Specifically, not only the number of repetitions of a movement, but also the details of the execution (in particular the acceleration profiles) should be analyzed. The ultimate goal is to make patients optimally manage the movement during a workout with respect to stimulating muscle building.