Project EU-TRAINS: Prof. Schumann and TUM researchers develop intelligent sensor technologies for easier performance and health diagnostics

How capable is the human body – and will it be possible in the future to answer this question without having to visit a laboratory? In the European collaborative project “EU-TRAINS,” researchers from the Chair of Experimental Exercise Science, led by Prof. Dr. Moritz Schumann, and research associate Lars Heinrich, are working with international partners to develop sensor and wearable technologies that capture physiological and neuromuscular data and analyze it using artificial intelligence. The goal is to make the assessment of physical performance simpler and more suitable for everyday use in the future.

“The idea is that, in the future, a small number of wearable sensors will be sufficient to draw conclusions about an individual’s performance capacity based on data collected during everyday life,” explains Prof. Schumann.

EU-TRAINS is funded by the European Commission with a total budget of around €7.8 million, of which €350,000 is allocated to TUM. The project aims to strengthen Europe’s value chain for sensors used in real-time monitoring of biomechanical and cardiovascular parameters and to advance applications in the fields of fitness and health. Among other things, the project combines intelligent textiles, miniaturized sensor systems, and AI-based methods for data processing. “We need to think on a European level. The idea is to make the European Union, as a whole, somewhat more independent from global partners,” says Prof. Schumann.

Today, accurately determining physical performance usually requires complex laboratory assessments. One of the most important parameters is maximum oxygen uptake (VO₂max), which describes how much oxygen the body can absorb and utilize during high-intensity exercise. Exercise thresholds are also important reference points for training control and assessing individual performance capacity. “At the moment, I can only test maximum oxygen uptake and threshold intensities in the laboratory,” explains Prof. Schumann. The aim of the project is therefore to develop an AI model that can reliably estimate these values in the future based on data from various sensors and wearables.

To achieve this, precise reference values are first collected in the laboratory. Participants complete standardized exercise tests on a treadmill, during which respiratory gases and blood lactate are analyzed, while heart rate, heart rate variability, oxygen saturation, muscle activity, and movement data are recorded. “We have a hardware component and a software component. The AI needs to be trained with data – and that is exactly the part we are responsible for,” says Prof. Schumann. The collected data will then be used to develop and validate AI models and to determine which variables and markers are actually relevant for assessing physical performance.

The researchers are not only examining individual measurements, but also the speed at which different physiological systems adapt to changes in workload. “When you change running speed – for example, when you walk slower or faster – all physiological systems adapt. The question is: How quickly do they adapt? And precisely this speed of adaptation provides information about how good someone’s performance capacity is,” explains Prof. Schumann. These so-called kinetics could provide additional insights into an individual’s fitness level.

As the project progresses, laboratory procedures will gradually be replaced by wearable sensor systems. The researchers are investigating whether the developed algorithms can also provide reliable results when data is collected under less controlled conditions using wearables. “Initially, the methods are developed and validated under controlled laboratory conditions. During the further course of the project, laboratory measurements will gradually be replaced by the wearable technologies developed within the project,” says the sports scientist.

In addition to its central focus on health and performance, EU-TRAINS also addresses further areas of application. These include sweat sensors, which will initially be tested under real-world conditions on humans, as well as sensor-based applications in swimming. Here, project partners are working, among other things, on communication between sensors underwater. In the future, such systems could provide information about swimming technique and give athletes direct feedback.

In the long term, the technologies developed within the project are intended to be used beyond competitive sports. Since maximum oxygen uptake (VO₂max) is considered an important indicator of overall health, wearable sensor systems could in the future help people measure their physical fitness more easily and regularly, thereby providing insights into their health status. “The fundamental idea is to eliminate the need for complex laboratory diagnostics and develop diagnostics that are accessible to everyone,” says Prof. Schumann.

An important part of the current research activities is the collection of data from participants, which has now begun as part of EU-TRAINS. Participants complete standardized exercise tests during which precise laboratory values are collected while data from various sensor systems and wearables is recorded simultaneously. These datasets will be used to develop and validate the AI model for estimating VO₂max and exercise thresholds.

Through collaboration between international research institutions and companies, EU-TRAINS brings together expertise across the entire technological value chain – from the development of sensors and microsystems to their integration into intelligent textiles and the processing of data using AI. “We need partners from different countries who have developed different systems and have different experiences with these systems,” explains Prof. Schumann. In the long term, the project aims to establish a comprehensive value chain for innovative sensor and wearable technologies within Europe.

To the website of the Chair of Experimental Ecercise Science
To the website of the EU-TRAINS project
To the registration for participants in the study

Contact

Prof. Dr. Moritz Schumann
Chair of Experimental Exercise Science
TUM Campus im Olympiapark
Am Olympiacampus 11
80809 Munich, Germany

Tel.: +49 (89) 289 – 24504
Email: moritz.schumann(at)tum.de

Text: Bastian Daneyko
Photo: Private