Improving Airline Pilots’ Visual Scanning and Manual Flight Performance through Training on Skilled Eye Gaze Strategies

Eye Tracking to Assess the Functional Consequences of Vision Impairment: A Systematic Review

BACKGROUND

Eye tracking is a promising method for objectively assessing functional visual capabilities, but its suitability remains unclear when assessing the vision of people with vision impairment. In particular, accurate eye tracking typically relies on a stable and reliable image of the pupil and cornea, which may be compromised by abnormalities associated with vision impairment (e.g., nystagmus, aniridia).

OBJECTIVES

This study aimed to establish the degree to which video-based eye tracking can be used to assess visual function in the presence of vision impairment.

DATA SOURCES

A systematic review was conducted using PubMed, EMBASE, and Web of Science databases, encompassing literature from inception to July 2022.

STUDY ELIGIBILITY CRITERIA, PARTICIPANTS, AND INTERVENTIONS

Studies included in the review used video-based eye tracking, included individuals with vision impairment, and used screen-based tasks unrelated to practiced skills such as reading or driving.

STUDY APPRAISAL AND SYNTHESIS METHODS

The included studies were assessed for quality using the Strengthening the Reporting of Observational Studies in Epidemiology assessment tool. Data extraction and synthesis were performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

RESULTS

Our analysis revealed that five common tests of visual function were used: (i) fixation stability, (ii) smooth pursuit, (iii) saccades, (iv) free viewing, and (v) visual search. The studies reported considerable success when testing individuals with vision impairment, yielding usable data from 96.5% of participants.

LIMITATIONS

There was an overrepresentation of conditions affecting the optic nerve or macula and an underrepresentation of conditions affecting the anterior segment or peripheral retina.

CONCLUSIONS AND IMPLICATIONS OF KEY FINDINGS

The results offer promise for the use of eye tracking to assess the visual function of a considerable proportion of those with vision impairment. Based on the findings, we outline a framework for how eye tracking can be used to test visual function in the presence of vision impairment.

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

Pilots' loss of situational awareness is one of the human factors affecting aviation safety. Numerous studies have shown that pilot perception errors are one of the main reasons for a lack of situational awareness without a proper system to detect these errors. The main objective of this study is to examine the changes in pilots' eye movements during various flight tasks from the perspective of visual awareness. The pilot's gaze rule scanning strategy is mined through cSPADE, while a hidden semi-Markov model-based model is used to detect the pilot's visuoperceptual state, linking the correlation between the hidden state and time. The performance of the proposed algorithm is then compared with that of the hidden Markov model (HMM), and the more flexible hidden semi-Markov model (HSMM) is shown to have an accuracy of 93.55%.

Visualizing a Task Performer’s Gaze to Foster Observers’ Performance and Learning—a Systematic Literature Review on Eye Movement Modeling Examples

Eye movement modeling examples (EMMEs) are instructional videos (e.g., tutorials) that visualize another person’s gaze location while they demonstrate how to perform a task. This systematic literature review provides a detailed overview of studies on the effects of EMME to foster observers’ performance and learning and highlights their differences in EMME designs. Through a broad, systematic search on four relevant databases, we identified 72 EMME studies (78 experiments). First, we created an overview of the different study backgrounds. Studies most often taught tasks from the domains of sports/physical education, medicine, aviation, and STEM areas and had different rationales for displaying EMME. Next, we outlined how studies differed in terms of participant characteristics, task types, and the design of the EMME materials, which makes it hard to infer how these differences affect performance and learning. Third, we concluded that the vast majority of the experiments showed at least some positive effects of EMME during learning, on tests directly after learning, and tests after a delay. Finally, our results provide a first indication of which EMME characteristics may positively influence learning. Future research should start to more systematically examine the effects of specific EMME design choices for specific participant populations and task types.