态度跟踪中的多模态提示:通过生理测量预测飞行员心理负荷

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

Human Factors The Journal of the Human Factors and Ergonomics Society · 2025
被引 0
ABS 3

中文导读

研究了直升机姿态跟踪任务中,不同视觉、听觉和触觉提示组合下生理信号与心理负荷的关系,发现多模态提示可降低认知负荷,有助于提升飞行安全。

Abstract

ObjectiveTo investigate the relationship between variations in physiological signals and mental workload (MWL) during the execution of a helicopter roll-attitude compensatory tracking task.BackgroundCurrent perceptual models in human-machine piloting have been focused on visual and vestibular cues, overlooking somatosensory and auditory inputs and their interactions. This creates a knowledge gap in understanding shared perception strategies for piloting in environments with impaired sensory channels or enhanced secondary cues.MethodsFifteen healthy participants performed an attitude-tracking task under eleven cueing modalities combining visual, degraded visual, haptic, and auditory cues. Physiological signals-cardiac activity, respiration, brain activity, skin temperature, and electrodermal activity-were analyzed in relation to self-reported MWL using statistical tests and GLMM (Generalized Linear Mixed Models).ResultsParticipants reported low perceived MWL under good visual conditions, with supplementary auditory and haptic cues helping to reduce MWL with degraded or absent visual input. Physiological signals discriminated between MWL levels and multivariate analysis showed that while combined signals revealed an evident explanation of their variance, individual differences underscored the importance of personalized modeling.ConclusionMWL assessment through physiological signals validated during a helicopter tracking task demonstrated that multimodal cueing in complex scenarios can reduce cognitive load, leading to potential safety risk mitigation.ApplicationThis research has the objective of providing a novel approach for safety enhancement and mitigating risks in rotorcraft operations by integrating visual, auditory, and somatosensory cues with physiological-based MWL assessment.

人机交互航空心理学生理信号分析心理负荷评估