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Researchers at ETH Zurich and ZHAW present a simple method to precisely map resistance exercise on machines and record missing comparative figures. This could help to develop optimised training strategies in the future, such as for age-associated muscular atrophy.
Muscles play a critical role in life. Skeletal muscle mass alone accounts for up to 40 percent of our body mass. Muscles turn chemical energy into mechanical energy and generate the power with which we breathe and move.
It is generally understood that physical activity can stimulate muscle growth. Resistance training is thus the key measure to counteract the negative effects of sarcopenia. However, what exactly targeted muscle training is and how it can optimally achieve its purpose is largely unknown.
“This is because resistance training is not mapped accurately enough in practice, so it is difficult to draw conclusions about muscle growth,” says Claudio Viecelli, PhD student at ETH's Institute of Molecular Systems Biology under Professor Ernst Hafen.
Viecelli aims to close this gap. For his dissertation, the molecular and muscle biologist worked with colleagues from Zurich University of Applied Sciences (ZHAW) and Kieser Training AG to develop an impressively simple method: it uses acceleration sensors in conventional smartphones to record resistance training variables on devices in a high temporal resolution. The researchers discussd their method in the specialist journal PLOS ONE.