Bayesian classification for bed posture detection based on kurtosis and skewness estimation

Chi Chun Hsia, Yu Wei Hung, Yu Hsien Chiu, Chia Hao Kang

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

28 Citations (Scopus)

Abstract

This study proposes a bed posture detection method using Bayesian classification for the elderly and bedridden. Only 16 long-narrow FSR (Force Sensing Resistor) sensors, rather than pressure distribution image from a set of sensor array are used for classification. Kurtosis and skewness are estimated as feature vector to represent the shape of pressure contour using the pressure values received from sensors. Gaussian distribution is adopted for statistical modeling and classification for bed postures including supine, left/right lying. Experimental results reveal that proposed method exhibits encouraging potential in bed posture detection.

Original languageEnglish
Title of host publication2008 10th IEEE Intl. Conf. on e-Health Networking, Applications and Service, HEALTHCOM 2008
Pages165-168
Number of pages4
DOIs
Publication statusPublished - 2008 Oct 6
Event2008 10th IEEE Intl. Conf. on e-Health Networking, Applications and Service, HEALTHCOM 2008 - Singapore, Singapore
Duration: 2008 Jul 72008 Jul 9

Publication series

Name2008 10th IEEE Intl. Conf. on e-Health Networking, Applications and Service, HEALTHCOM 2008

Conference

Conference2008 10th IEEE Intl. Conf. on e-Health Networking, Applications and Service, HEALTHCOM 2008
CountrySingapore
CitySingapore
Period08-07-0708-07-09

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Health Informatics
  • Health Information Management

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