How much do you read? - Counting the number of words a user reads using electrooculography

Kai Kunze, Katsutoshi Masai, Yuji Uema, Masahiko Inami

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

We read to acquire knowledge. Reading is a common activity performed in transit and while sitting, for example during commuting to work or at home on the couch. Although reading is associated with high vocabulary skills and even with increased critical thinking, we still know very little about effective reading habits. In this paper, we argue that the first step to understanding reading habits in real life we need to quantify them with affordable and unobtrusive technology. Towards this goal, we present a system to track how many words a user reads using electrooculography sensors. Compared to previous work, we use active electrodes with a novel on-body placement optimized for both integration into glasses (or head-worn eyewear etc) and for reading detection. Using this system, we present an algorithm capable of estimating the words read by a user, evaluate it in an user independent approach over experiments with 6 users over 4 different devices (8′ and 9′ tablet, paper, laptop screen). We achieve an error rate as low as 7% (based on eye motions alone) for the word count estimation (std = 0.5%).

Original languageEnglish
Title of host publicationACM International Conference Proceeding Series
PublisherAssociation for Computing Machinery
Pages125-128
Number of pages4
Volume11
ISBN (Print)9781450333498
DOIs
Publication statusPublished - 2015 Mar 9
Event6th Augmented Human International Conference, AH 2015 - Singapore, Singapore
Duration: 2015 Mar 92015 Mar 11

Other

Other6th Augmented Human International Conference, AH 2015
Country/TerritorySingapore
CitySingapore
Period15/3/915/3/11

Keywords

  • EOG
  • Eye movement analysis
  • Reading
  • Wordcount

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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