Non-Invasive Screen Exposure Time Assessment Using Wearable Sensor and Object Detection

Xueshen Li, Steven Holiday, Matthew Cribbet, Anirudh Bharadwaj, Susan White, Edward Sazonov, Yu Gan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Cumulative screen exposure has been increased due to the explosion of digital technology ownership in the past decade for all people, including children who face exposure related risks such as obesity, eye problems, and disrupted sleep. Screen exposure is linked to physical and mental health risks among both children and adults. Current methods of screen exposure assessment have their limitations, mostly in the prospective of objectiveness, robustness, and invasiveness. In this paper, we propose a novel method to measure screen exposure time using a wearable sensor and computer vision technology. We use a customized, lightweight, wearable senor to capture egocentric images and use deep learning-based object detection module to identify the existence of electronic screens. The duration of screen exposure is further estimated using post-processing technology to filter consecutive frames regarding to the screen usage. Our method is non-invasive and robust, providing an objective and accurate means to screen exposure measurement. We conduct experiments on various environments to identify the existence of three types of screens and duration of screen exposure. The experimental results demonstrate the feasibility of automatically assessing screen time exposure and great potential to be applied in large scale experiments for behavioral study.

Original languageEnglish
Title of host publication44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022
Pages4917-4920
Number of pages4
ISBN (Electronic)9781728127828
DOIs
StatePublished - 2022
Event44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022 - Glasgow, United Kingdom
Duration: 11 Jul 202215 Jul 2022

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2022-July
ISSN (Print)1557-170X

Conference

Conference44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022
Country/TerritoryUnited Kingdom
CityGlasgow
Period11/07/2215/07/22

Keywords

  • Computer vision
  • Object detection
  • Screen exposure measurement
  • Wearable sensors

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