The centre of the research is multimodal brain-body systems, artificial intelligence, digital signal processing and neurotechnology. It investigates how the brain, body, behaviour and situational context can be characterised and modelled as an interconnected dynamic system. The aim is to gain a comprehensive understanding of their interactions and to harness them for clinical and everyday applications. To this end, neurophysiological methods such as fNIRS, EEG and fMRI, as well as multimodal combinations such as fNIRS-EEG and fMRI-fNIRS, are linked with peripheral physiological signals, movement and activity data, and information from wearables and smartphones. Multimodality refers to the integration of complementary information about the brain, the body, behaviour and everyday life.

A key methodological focus lies on artificial intelligence and machine learning. These methods make it possible to identify complex patterns and interactions in multimodal data, to integrate different data sources, to model individual changes over time and to predict relevant states. This involves combining data-driven methods with robust digital signal processing, physiological knowledge and statistical modelling. Another focus is on real-time systems. The continuous processing of multimodal data makes it possible to detect changes immediately and adapt technical systems to a person’s current state and context. This lays the foundation for adaptive neurotechnologies such as neurofeedback and brain-computer interfaces, as well as for digital monitoring and personalised support.

A key vision is the transfer of research from controlled laboratory conditions to clinical, real-life and home-based application contexts. The integration of neurophysiological, physical, behavioural and contextual data opens up new possibilities for digital phenotyping, digital biomarkers, monitoring, early detection and individualised interventions. Key areas of application lie particularly in the field of mental health, as well as in neurology and rehabilitation. This perspective also forms the scientific basis of the Multimodal Brain-Body Systems research group.