Researchers take step towards digitalized gym

Until now, activity carried out during a weight training session has usually been logged in terms of sets and repetitions. However, such training data is insufficiently comparable and thus sub-​optimal when it comes to examining the effects of training on muscle growth, the Swiss Federal Institute of Technology in Zurich (ETH) explained in a press release.

The temporal patterns of resistance training are relevant to muscle plasticity. This means it is important to describe the “single repetition”, which consists of lifting and lowering the load. Also key are the “contraction-​phase specific time”, so the time the muscle is under tension during the lifting and lowering, and quantifying the “total time-​under-tension”.

Researchers at ETH and the Zurich University of Applied Sciences (ZHAW) have now  developed a simple method for determining these various elements. The method uses acceleration sensors in conventional smartphones. They attached the smartphone to the weight stack and an app then logged the sensor data. The researchers were then able to determine the contraction times from these acceleration profiles.

According to ETH, the new analysis method enables resistance exercises to be mapped much more accurately. The method is primarily intended for research purposes. It could be used to develop optimized training strategies for age-​associated muscular atrophy, for example. Later, the method might also help in creating digitalized resistance training facilities, allowing training programs to be better tailored to individual needs.