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Towards non-intrusive sleep pattern recognition in elder assistive environment

  • Hongbo Ni
  • , Bessam Abdulrazak
  • , Daqing Zhang
  • , Shu Wu
  • , Zhiwen Yu
  • , Xingshe Zhou
  • , Shengrui Wang
  • Northwestern Polytechnical University
  • Université de Sherbrooke

Résultats de recherche: Contribution à un journalArticleRevue par des pairs

12 Citations (Scopus)

Résumé

Quality of sleep is an important attribute of an elder's health state and its assessment is still a challenge. The sleep pattern is a significant aspect to evaluate the quality of sleep, and how to recognize elder's sleep pattern is an important issue for elder-care community. With the pressure sensor matrix to monitor the elder's sleep behavior in bed, this paper presents an unobtrusive sleep postures detection and pattern recognition approaches. Based on the proposed sleep monitoring system, the processing methods of experimental data and the classification algorithms for sleep pattern recognition are also discussed.

langue originaleAnglais
Pages (de - à)167-175
Nombre de pages9
journalJournal of Ambient Intelligence and Humanized Computing
Volume3
Numéro de publication2
Les DOIs
étatPublié - 1 juin 2012

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