Smart cushion: A practical system for fine-grained sitting posture recognition

Guanqing Liang, Jiannong Cao, Xuefeng Liu

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

9 Citations (Scopus)

Abstract

Poor sitting postures influence one's health and can cause upper limb and neck disorder. Current solutions for siting posture recognition, however, are impractical due to intrusiveness, high cost or low generalization capability. Particularly, most of the existing solutions are chair-dependent, which are highly coupled with certain types of chairs. In this paper, we design Postureware, a smart cushion, which is a low-cost, non-intrusive and general sitting posture recognition system. In particular, Postureware incorporates very thin pressure sensors to offer non-intrusive experience, an effective sensor placement solution to reduce cost, a set of user-invariant features and an ensemble learning classifier to improve generalization ability. We implement a prototype system and conduct extensive experiments. The results show that Postureware can classify fifteen fine-grained postures with high accuracy.
Original languageEnglish
Title of host publication2017 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2017
PublisherIEEE
Pages419-424
Number of pages6
ISBN (Electronic)9781509043385
DOIs
Publication statusPublished - 2 May 2017
Event2017 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2017 - Kona, Big Island, United States
Duration: 13 Mar 201717 Mar 2017

Conference

Conference2017 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2017
Country/TerritoryUnited States
CityKona, Big Island
Period13/03/1717/03/17

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications

Cite this