Self-configuring, ambulatory motion capturing and analysis
Objectives and approaches
The aim of this line of research is to provide a system based on wearable sensors (inertial measurement units, pressure insoles) that captures relevant kinematic, kinetic, and spatiotemporal movement parameters in real-time and measures these in an objective, reliable, and valid way. Based on this, the system should be able to provide context- and user-adapted analyses, while context here, for example, refers to the user’s current activity, i.e., the person wearing the sensors. At the same time, the system should be flexible, i.e., adjustable to different body parts, parameters, or individual reference values, and easy to use. In order to increase the usability and reduce errors, one focal point is the provision of a self-configuring system that automatically adjusts itself to the anthropometric characteristics of the user while also adjusting itself to the sensor positioning relative to the user’s body. To achieve this, new models, methods, and systems are being developed, implemented, and evaluated. These use model-based probabilistic estimation, optimal control, and machine learning approaches.
Design, implementation, and evaluation of new models and methods are carried out in cooperation between mathematics, computer science, movement science, and control engineering. The requirements analysis as well as the design and the evaluation of studies are supported by psychologists and cognitive scientists. Research questions concerning the extraction of anthropometric information from camera images as well as questions concerning machine learning are investigated in cooperation with the Department Augmented Vision at the German Research Center for Artifical Intelligence (DFKI). For questions regarding the connection of lightweight and reliable body sensor networks, we also cooperate with the Department Augmented Vision at DFKI as well as with the Microelectronic Systems Design Research Group at Technische Universität Kaiserslautern (TUK). For biomechanical issues, we cooperate with the Department of Movement and Training Science at TUK as well as with the Klinik Lindenplatz. Regarding medical and application-specific questions, we also cooperate with the Klinik Lindenplatz and with the University Hospital Halle (Saale). Research questions regarding the coupling of sensor measurements and optimal control methods are investigated in collaboration with the Chair of Applied Dynamics at the University of Erlangen-Nuremberg. Mathematical modeling issues are investigated in cooperation with the research group Technomathematics at TUK. In cooperation with the Chair of Control Systems at TUK we develop methods for motion prediction in the context of human-robot-interaction.
Customizable, motivating user interfaces for mobile training support
Objectives and approaches
The goal of this line of research is the iterative and user-centered development and validation of interactive mobile user interfaces for personalized training support throughout the rehabilitation process. For this purpose, the user interfaces are first connected to the self-configuring, ambulatory motion capturing and analysis. In order to support motivation and adherence, current concepts such as gamification and exergames are used. Furthermore, the control of correct movement or exercise execution via multi-modal feedback plays an important role in the design process. In addition to international standards (e.g., DIN EN ISO 9241), current research results in the context of age-based information visualization are also taken into account and are further developed for the described application scenario. An essential component of the entire development process is the continuous integration of the user, where usability and technology acceptance are particularly evaluated.
The user interfaces are developed in close coordination between computer science, mathematics, movement science, psychology, and cognitive science. The former disciplines realize the integration of the self-configuring, ambulatory motion capturing and analysis, while the psychologists and cognitive scientists support the iterative development process in the areas of study design and evaluation. Regarding medical and application-specific questions, we cooperate with the Westpfalz-Klinikum, the Klinik Lindenplatz and the Outpatient Rehabilitation Center in Kaiserslautern as well as with the company Ergo-Fit.
Customizable, motivating user interface for sustainable health-related behavioral changes
Objectives and approaches
The objective of this line of research is the development of mobile applications (apps), which support the development of health-conscious behavior and the learning of effective stress management methods within a defined period of use. In order to achieve this, effective relaxation techniques are combined with proven behavioral change techniques and gamification elements. The gamification elements serve the purpose of increasing the joy of use. Furthermore, some relaxation tasks will be combined with biofeedback realized via wearables (e.g., a portable EEG system or accelerometers). The development is accompanied by regular surveys, interviews, cross-sectional and longitudinal user studies, as well as experimental study designs. Here, the focus is on the evaluation of usability, user experience, technology acceptance and effectiveness.
Design, implementation and evaluation of the user interfaces are carried out in close cooperation between psychology, cognitive science, and computer science. The latter discipline, besides implementation in general, contributes in particular to the development and implementation of the gamification elements. Data processing based on wearables is also supported by mathematics. EEG research takes place in cooperation with the Center for Cognitive Science at the Technische Universität Kaiserslautern. Research questions concerning three-dimensional avatars are dealt with in collaboration with the RODOS AG at the Fraunhofer ITWM. The group's health app Stress-Mentor is available for free for Android devices since February 2019 (German language only for now). Since 2017, this app is further developed for the accompanying use during rehabilitation for chronic pain patients (Schmerz-Mentor) in cooperation with the University Hospital Halle (Saale) (Dr. Katja Regenspurger).