Cushionware: A practical sitting posture-based interaction system

Guanqing Liang, Jiannong Cao, Xuefeng Liu, Xu Han

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

9 Citations (Scopus)


Sitting posture-based interaction is to leverage user's sitting posture as an input for interaction. In order to realize it, user's sitting posture needs to be recognized accurately. However, existing works on sitting posture recognition either use intrusive wearable/visual sensors or rely on expensive high-resolution pressure sensor array, and thus hindering the widespread adoption. In this work, we introduce Cushionware, a practical sitting posture recognition system that is based on sparse pressure sensor array. Pressure sensor array is placed within the chair cushion to collect pressure data while user is sitting. After collecting the data, we first model sitting posture by extracting a set of user-invariant features and then identify the sitting posture using machine learning method. To demonstrate the utility of Cushionware, we develop two applications including video game playing and wheelchair motion control.
Original languageEnglish
Title of host publicationCHI EA 2014
Subtitle of host publicationOne of a ChiNd - Extended Abstracts, 32nd Annual ACM Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
Number of pages4
ISBN (Print)9781450324748
Publication statusPublished - 1 Jan 2014
Event32nd Annual ACM Conference on Human Factors in Computing Systems, CHI EA 2014 - Toronto, ON, Canada
Duration: 26 Apr 20141 May 2014


Conference32nd Annual ACM Conference on Human Factors in Computing Systems, CHI EA 2014
CityToronto, ON


  • Natural user interface
  • Sitting posture

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

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