Driver fatigue is one of the main causes of road accidents. It is essential to develop a reliable driver drowsiness detection system which can alert drivers without disturbing them and is robust to environmental changes. This paper explores yawning behaviour as a sign of drowsiness in spontaneous expressions of drowsy drivers in simulated driving scenarios. We analyse a labelled dataset of videos of sleep-deprived versus alert drivers and demonstrate the correlation between handover-face touches, face occlusions and yawning. We propose that face touches can be used as a novel cue in automated drowsiness detection alongside yawning and eye behaviour. Moreover, we present an automatic approach to detect yawning based on extracting geometric and appearance features of both mouth and eye regions. Our approach successfully detects both hand-covered and uncovered yawns with an accuracy of 95%. Ultimately, our goal is to use these results in designing a hybrid drowsiness-detection system.
PurposeThis study aims to reveal how mobile app stickiness is formed and how the stickiness formation process differs for apps of different social levels.Design/methodology/approachThis study proposed and validated a stickiness formation model following the cognitive–affective–conative framework. Data were collected from surveys of 1,240 mobile app users and analyzed using structural equation modeling. Multigroup analysis was applied to contrast the stickiness formation process among apps of different social levels.FindingsThis study revealed a causal link between cognitive, affective and conative factors. It found partial mediation effects of trust in the association between perceptions and satisfaction, and the full mediation role of satisfaction and personal investment (PI) in the effects of subjective norm (SN) on stickiness. The multigroup analysis results suggested that social media affordances benefit stickiness through increased PI and strengthened effects of SN on PI. However, it damages stickiness through increased perceived privacy risk (PPR), decreased trust and strengthened effects of PPR on trust.Originality/valueThis study contributes to both stickiness scholars and practitioners, as it builds a model to understand the stickiness formation process and reveals the effects of the “go social” strategy. The novelty of this study is that it examined social influences, considered privacy issues and revealed two mediation mechanisms. The findings can guide the improvement of mobile app stickiness and the application of the “go social” strategy.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.