Abnormality detection for improving elder's daily life independent

Ya Xuan Hung*, Chih Yen Chiang, Steen J. Hsu, Chia Tai Chan

*Corresponding author for this work

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

31 Scopus citations

Abstract

Since the dramatic demographic change makes it inevitable that rapid aging of the population is an unprecedented phenomenon in Taiwan. A growing social problem is supporting older adults who want to live independently in their own homes. It needs a health assistance system to make them independent living up to a higher age. Recently, technological advancements have spurred various ideas and innovations to assist the elders living independently. In this paper, we proposed a homecare sensory system that uses RFID-based sensor networks to collect elder's daily activities and conducts the data into Hidden Markov model (HMM) and Support Vector Machines (SVMs) to estimate whether the elder's behavior is abnormal or not. Through detecting and distinguishing the abnormal behaviors of elder's daily activities, the system provides assistance on elder's independent living and improvement of aged quality of life.

Original languageEnglish
Title of host publicationAging Friendly Technology for Health and Independence - 8th International Conference on Smart Homes and Health Telematics, ICOST 2010, Proceedings
Pages186-194
Number of pages9
DOIs
StatePublished - 2010
Event8th International Conference on Smart Homes and Health Telematics, ICOST 2010 - Seoul, Korea, Republic of
Duration: 22 Jun 201024 Jun 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6159 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Smart Homes and Health Telematics, ICOST 2010
Country/TerritoryKorea, Republic of
CitySeoul
Period22/06/1024/06/10

Keywords

  • HMM
  • RFID
  • SVM
  • abnormal activity

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