Multi-modal non-intrusive sleep pattern recognition in elder assistive environment

Hongbo Ni, Bessam Abdulrazak, Daqing Zhang, Shu Wu, Xingshe Zhou, Kejian Miao, Daifei Han

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Quality of sleep is an important attribute of an elder's health state and its assessment is still a challenge. Sleep pattern is a significant aspect to evaluate the quality of sleep, and how to recognizethe elder's sleep pattern is an importantissuefor elder-care community. This paper presents a novel multimodal sensing system to monitor the elder's sleep behavior with the pressure sensor matrix and ultra wide band (UWB) tags.Based on the proposed sleep monitoring system, the paper addresses the unobtrusive sleep postures detection and pattern recognition approaches, and the processing methods of experimental data and theclassification algorithms for sleep pattern recognitionare also discussed.

Original languageEnglish
Title of host publicationImpact Analysis of Solutions for Chronic Disease Prevention and Management - 10th International Conference on Smart Homes and Health Telematics, ICOST 2012, Proceedings
Pages132-139
Number of pages8
DOIs
StatePublished - 2012
Event10th International Conference on Smart Homes and Health Telematics, ICOST 2012 - Artimino, Italy
Duration: 12 Jun 201215 Jun 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7251 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International Conference on Smart Homes and Health Telematics, ICOST 2012
Country/TerritoryItaly
CityArtimino
Period12/06/1215/06/12

Keywords

  • Elder-care
  • Naïve Bayes Tree
  • Pressure Sensor
  • Random Forest
  • Sleep Pattern
  • UWB tags

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