Multimodal Cueing in Attitude Tracking: Predicting Pilot Mental Workload Through Physiological Measurements.

Area of Science:

• Human-computer interaction
• Aerospace engineering
• Cognitive neuroscience

Background:

• Current piloting models neglect somatosensory and auditory inputs, creating a gap in understanding perception.
• This limits knowledge of shared perception strategies, especially with impaired sensory channels.

Purpose of the Study:

• To explore the link between physiological signals and mental workload (MWL) during helicopter piloting.
• To assess how multimodal cueing affects MWL and pilot performance.
• To validate physiological measures for MWL assessment in aviation.

Main Methods:

• Fifteen participants performed a helicopter roll-attitude compensatory tracking task.
• Eleven cueing modalities combining visual, haptic, and auditory stimuli were used.
• Physiological signals (cardiac, respiratory, brain activity, skin temperature, electrodermal) were analyzed against self-reported MWL using GLMM.

Main Results:

• Multimodal cueing, especially auditory and haptic, reduced MWL with degraded visual input.
• Physiological signals effectively differentiated between MWL levels.
• Individual differences highlighted the need for personalized MWL modeling.

Conclusions:

• Physiological signal assessment during a helicopter task confirms multimodal cueing reduces cognitive load in complex scenarios.
• This approach can mitigate safety risks in rotorcraft operations.
• Integrating sensory cues with physiological MWL assessment offers a novel safety enhancement strategy.