Automated Data Gathering and Training Tool for Personalized "itchy Nose"

Juyoung Lee, Hui Shyong Yeo, Thad Starner, Aaron Quigley, Kai Kunze, Woontack Woo

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

2 Citations (Scopus)


In "Itchy Nose" we proposed a sensing technique for detecting finger movements on the nose for supporting subtle and discreet interaction. It uses the electrooculography sensors embedded in the frame of a pair of eyeglasses for data gathering and uses machine-learning technique to classify different gestures. Here we further propose an automated training and visualization tool for its classifier. This tool guides the user to make the gesture in proper timing and records the sensor data. It automatically picks the ground truth and trains a machine-learning classifier with it. With this tool, we can quickly create trained classifier that is personalized for the user and test various gestures.

Original languageEnglish
Title of host publicationProceedings of the 9th Augmented Human International Conference, AH 2018
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450354158
Publication statusPublished - 2018 Feb 6
Externally publishedYes
Event9th Augmented Human International Conference, AH 2018 - Seoul, Korea, Republic of
Duration: 2018 Feb 72018 Feb 9

Publication series

NameACM International Conference Proceeding Series


Other9th Augmented Human International Conference, AH 2018
Country/TerritoryKorea, Republic of


  • EOG
  • Nose gesture
  • Online classification
  • Smart eyeglasses
  • Smart eyewear
  • Subtle interaction
  • Training tool
  • Wearable computer

ASJC Scopus subject areas

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


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