Methoden zur adaptiven Benutzerinteraktion bei der semi-autonomen Aufgabenbearbeitung in Rehabilitationsszenarien

The ever increasing performance of modern computing systems enables the realization of more challenging functionalities in software and mechatronic systems. This tendency results in an increase in system complexity and also makes the operation by users more difficult. Therefore, recent developments are focusing more strongly on the usability of technical systems, especially in case of systems that do not only communicate with users via a user interface but also interact with them physically. Systems that support social reintegration of persons with disabilities, so-called rehabilitation or support robots, fall into this area. This thesis focuses on the development of methods for adaptive user interactions within a software architecture for rehabilitation robots. The objective is the development of a software framework that acts as a basis for the adaptability of the graphical user interface. The methods presented to realize adaptivity are based on a user interface modularization by encapsulating all functionalities into modules. These modules can be activated or deactivated during run-time depending on the availability of resources. Furthermore, a bi-directional communication channel between the user interface and active modules as well as among modules is established. Thus it becomes possible to source common functionality out into modules and to have it reused by other modules. The communication is based on a specification language that has been developed to enable validation and to reach robust run-time behavior. An extensive review of the software architecture used for the target system identified open problems that previously prevented the realization of adaptivity within the user interface. By using another specification language, finding solutions for those open problems becomes possible as well as achieving the set objective. The development is based on an abstraction layer between the user interface and the remaining layers of the software architecture. This realizes full decoupling of the user interface from system specificfunctionality. To proof the concept for adaptivity within the user interface, the implementation of a module integrating an algorithm for pattern recognition is exemplarily shown with the aim to predict future actions of the user by evaluating previous actions