Development of an assistant system for regulating the mental strain state of agricultural machinery operators
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Beschreibung
The increasing automation of agricultural machinery leads to fluctuating phases of mental underload and overload for operators, impairing performance, safety, and well-being. This dissertation evaluates an adaptive assistance system that monitors and regulates mental strain in real time. Using a combine harvester, multimodal sensor data trained a model to classify mental states. A virtual assistant provides task recommendations. Studies show improved strain regulation and practical applicability.
Autor*in
Steffen Metzger
Themen in »Development of an assistant system for regulating the mental strain state of agricultural machinery operators«
Adaptive Assistenzsysteme Kognitive Beanspruchung Virtueller Assistent Ergonomie Mensch-Maschine-Schnittstelle Adaptive assistance systems Mental strain Virtual assistant Ergonomics Human-machine interface