HUTwin aims to create model-based interacting digital twins (DTs) to understand the human–device interaction. Digital Twins are becoming common in predictive maintenance of complex systems like jet or wind turbines. These twins are mainly based on sensor information of the real system during lifetime. The Twin tries to predict the behaviour of the system and by this predict the required maintenance actions during lifetime. This is an a posteriori twin because the system has to physically exist before any information from the system can be gathered. In our case the twin is an a priori description because the models, mostly complex physics-based finite element (FE) models, have been developed prior to (manufacturing of) the real system and the twin that is based on this simulation. Having an a priori DT strengthens the development phase of the product, for example to optimize the developed solution or to get more in-depth understanding of the product. The twin will help to speed up the innovation process, can help the engineering process, and can predict quality and reliability of the produced system. It can even customise products by implementing a subset of the twin as a part of the product-human interaction. The Twin itself will be a combination of artificial intelligence and physical based modelling, optimised during the lifetime by real-time information of the embedded sensors. A special case of Twins are those that try to predict the human-device interaction either in the development phase or during the lifetime of the device. In principle the device can be anything, a simple consumer product, a personal health device, a complex system like a CT scanner or even a robot or cobot in a production platform.