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Related Experiment Video

Updated: Jul 20, 2025

Evaluating Flight Performance and Eye Movement Patterns Using Virtual Reality Flight Simulator

Evaluating Flight Performance and Eye Movement Patterns Using Virtual Reality Flight Simulator

Published on: May 19, 2023

Hidden Semi-Markov Models-Based Visual Perceptual State Recognition for Pilots.

Lina Gao¹, Changyuan Wang², Gongpu Wu¹

¹Optical Engineering, Xi'an Technological University, Xi'an 710021, China.

Sensors (Basel, Switzerland)

|July 29, 2023

Summary

This study introduces a novel method to detect pilot perception errors by analyzing eye movements, enhancing aviation safety. The hidden semi-Markov model achieved 93.55% accuracy in identifying visuoperceptual states, improving situational awareness.

Keywords:

hidden semi-Markov model state detection visual perception

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Last Updated: Jul 20, 2025

Evaluating Flight Performance and Eye Movement Patterns Using Virtual Reality Flight Simulator

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Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

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Published on: April 11, 2025

Area of Science:

Human Factors in Aviation
Cognitive Science
Aerospace Engineering

Background:

Pilot situational awareness is critical for aviation safety.
Perception errors are a significant cause of situational awareness loss.
Existing systems lack effective detection of pilot perception errors.

Purpose of the Study:

To investigate changes in pilots' eye movements during flight tasks.
To analyze visual scanning strategies and their relation to situational awareness.
To develop a system for detecting pilot visuoperceptual states.

Main Methods:

Utilized cSPADE to mine pilot gaze scanning strategies.
Employed a hidden semi-Markov model (HSMM) to detect visuoperceptual states.
Correlated hidden states with time and compared HSMM performance against hidden Markov models (HMM).

Main Results:

The proposed HSMM algorithm accurately detected pilot visuoperceptual states.
Achieved a high accuracy of 93.55% in performance.
Demonstrated the superior flexibility and accuracy of HSMM over HMM.

Conclusions:

The developed HSMM-based model effectively identifies pilot perception errors.
This approach can significantly enhance aviation safety by improving situational awareness.
Eye movement analysis offers a promising avenue for real-time monitoring of pilot cognitive states.