DINCO - Detection of Interaction Competencies and Obstacles

• Applicant: Dr. Felix Putze
• Subject Area: Human Factors, Ergonomics, Human-Machine Systems ; Image and Language Processing, Computer Graphics and Visualisation, Human Computer Interaction, Ubiquitous and Wearable Computing
• Term: from 2016 to 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 316930318

Technical systems are about to become an important part of the daily life of olderpeople as well as a crucial support tool. However, currently many older users face interaction obstacles which prevent them from benefitting from such systems. The current state-of-the-art of system interfaces are one-fits-all solutions. They follow design suggestions which do not take individual differences into account. Particularly for older users, this poses immense problems. We propose the novel DINCO method as an advancement: DINCO collects behavioral and physiological data during system usage which is passed on to a hierarchical statistical model. This model aggregates and interprets the user data to identify behavioral descriptors and generatehypotheses about existing interaction obstacles and interaction competencies. It then finds an optimal adaptation of the interface and finally automatically applies its hypothesis automatically to test and implement it.

• DFG Programme: Research Grants