[Design and validation of a computer-based task for the induction of a mental workload spectrum]

Area of Science:

• Human-Computer Interaction
• Cognitive Psychology
• Agricultural Engineering

Context:

• Developing adaptive human-machine interfaces (HMIs) for agricultural machinery is crucial for optimizing operator performance and safety.
• The driver's cab 4.0 project aims to create HMIs that adapt to the operator's cognitive state, specifically mental workload.
• Current methods for assessing mental workload in real-time within agricultural settings are limited.

Purpose:

• To design and evaluate an experimental task capable of inducing a spectrum of mental workload levels.
• To validate the task's effectiveness in differentiating between low, medium, and high mental workload conditions.
• To establish a foundation for developing a physiological indicator-based mental workload measurement system for agricultural machinery.

Summary:

• An experimental task involving a primary monitoring activity with adjustable visual and/or auditory secondary tasks was developed and evaluated.
• Three laboratory studies (N=17, N=8, N=21) demonstrated that this dynamic task combination significantly induced varying degrees of mental workload (F(2.40)=54.834, p<0.001).
• Subjective ratings (Rating Scale Mental Effort), reaction times, and error rates were used to quantify perceived mental workload.

Impact:

• The validated experimental task will be instrumental in creating a real-time mental workload measurement system for combine harvesters.
• This system aims to provide adaptive support, offering recommendations during low-workload phases (e.g., automated harvesting) and simplifying information display during high-workload phases.
• The ultimate goal is to reduce operator strain and enhance safety and efficiency in agricultural operations through intelligent HMI adaptation.