Study on the Operators’ Attention of Different Areas in University Laboratories Based on Eye Movement Tracking Technology

Zijun Li,Long Su,Shuqi Zhao,Chanjuan Liao

doi:10.1109/access.2020.2964907

Abstract

To explore different operators’ eye movement characteristics, which can reflect their degree of attention and hazard identification ability in university laboratories, experiments were carried out with 60 junior students. The laboratories were divided into five areas by function and hazard type. The subjects were divided into two groups based on their safety experience. Using typical university laboratory images as stimulus materials, a Tobii X2 eye tracker was used to measure and record the eye movement parameters of the subjects in five laboratory areas. The results showed that the subjects exhibited greater interest in the equipment area (attracting the focus of 100.00% of the subjects) and less interest in the wireway area (attracting the focus of 46.67% of the subjects); no significant difference was observed between subjects who were or were not specialized in safety. Most subjects could identify the hazard sources in the five areas but paid little attention to electrical sockets. Thus, countermeasures including reasonably matching the color and layout in laboratories and popularizing laboratory safety education are proposed, which will provide a basis for strengthening safety management in university laboratories.

Highlights

The university laboratory is an important place for experimental teaching and scientific research
The laboratories were divided into five regions according to their function, they are medicine area, equipment area, container area, wireway area, sign area, as it is shown in table 1
More than 90% of the subjects observed the five regions in the order of equipment area (B), container area (C), wireway area (D), medicine area (E), sign area (A)

Summary

Introduction

The university laboratory is an important place for experimental teaching and scientific research. Because of the environmental hazards and occurrence of personal operation errors, accidents occasionally occur in university laboratories. Data show that 98% of university laboratory safety accidents are caused by human factors [1], [2]. Large numbers of laboratory accidents have been reported worldwide, resulting in fatalities, severe injuries and financial losses, which demonstrates that there is a significant need for better identification of laboratory hazard sources and risk management practices within academic teaching and experimental research laboratories [3]. Many safety evaluation and analysis methods have been used for laboratory hazard source identification, such as risk matrix analysis [4], safety checklist [5], fuzzy evaluation and hazard evaluation and risk analysis.

Methods

Results

Conclusion