Technical systems become increasingly important for older people in their everyday life and support them in many situations. However, many older people, as systems users, have to struggle with interaction obstacles that prevent them from getting benefits from such systems. The state of the art user interfaces of such systems are one-fits-all solutions, i.e. their design does not consider individual differences between different users. This is a major problem especially for older people as psers of such interfaces. We propose the DINCO method to improve this situation: DINCO collects behavioral and physiological data of a user during his or her interaction with the technical system. These data are processed with a hierarchical statistical model. This model aggregates and interprets the collected data to extract behavioral descriptors which help the model to establish hypotheses about existing interaction obstacles and interaction competencies. DINCO derives from these hypotheses the optimal adaptation of the user interface and tests the hypotheses automatically by applying the adaptation.
Running time: 2016 – 2019
Contact person: Dr. Felix Putze, Mazen Salous