Upper limb prostheses have undergone continuous technological development over the past decades. Today’s prostheses already partially exploit the possibilities of biosignal analysis and pattern recognition to use e.g. muscle activity in the form of surface electromyography (sEMG) to control the prosthesis. Nevertheless, the rejection rate of electromyography-based interfaces remains very high. In the case of prostheses reasons for rejection often include HMI-related motives such as comfort, function, and control of the prosthesis. Consequently, many amputees use cosmetic or body-powered prostheses instead of the technologically advanced alternatives. The AIROB Lab researches and works continuously towards solving the mentioned problems, especially in the context of human-machine-interaction (HMI). The focus here is in particular the improvement of intent detection through sensor modalities, biosignal analysis and machine learning for the control of prostheses.