English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

From several investigations, it has been shown that most of the traffic accidents were due to drowsy driving. In order to address this issue, many related works have been conducted. One study was able to capture the driver’s facial expression and estimate their drowsiness. Instead of measuring the driver’s physiological condition, the results of such measurements were also used to predict their drowsiness level in this study. We investigated the relationship between the drowsiness and physiological condition by employing an eye gaze signal utilizing an eye gaze tracker and the Japanese version of the Karolinska sleepiness scale (KSS-J) within the driving simulator environment. The results showed that the gazing time has a significant statistical difference in relation to the drowsiness level: alert (1−5), weak drowsiness (6−7), and strong drowsiness (8−9), with P<0.001. Therefore, we suggested the potential of using the eye gaze to assess the drowsiness under a driving condition.

Gazing Time Analysis for Drowsiness Assessment Using Eye Gaze Tracker