Method of behavior modeling for detection of anomaly behavior using hidden Markov model

Haruka Ishii, Keisuke Kimino, Masahiro Inoue, Masaki Arahira, Yayoi Suzuki

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

6 Citations (Scopus)

Abstract

Dementia is disorder of memory and judgment caused by dying brain cells. Most of dementia symptoms can be only detected by housemates when they notice some changes in behaviors of elderly people. Therefore, it is difficult to detect the early symptoms of dementia in elderly people living alone. We focused on wandering which is typical symptom of dementia. We proposed the system to detect wandering symptom based on sensors data using Hidden Markov Model (HMM). We installed sensors to acquire elderly people behavior. Then, we created normal behavior model based on these sensors data using HMM. After that, we compare between this pattern model and detected behavioral pattern. When the detected behavioral pattern did not much with this pattern model, the system will classify the behavior as a wandering symptom. In this paper, we proposed the method which is a creation of normal behavior model. We verified whether our proposal method can estimate behavioral tendency of healthy elderly subject's living alone using two months' sensor data. The result suggested that this method can create a behavior model with considering about subject's habits.

Original languageEnglish
Title of host publicationInternational Conference on Electronics, Information and Communication, ICEIC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-4
Number of pages4
Volume2018-January
ISBN (Electronic)9781538647547
DOIs
Publication statusPublished - 2018 Apr 2
Event17th International Conference on Electronics, Information and Communication, ICEIC 2018 - Honolulu, United States
Duration: 2018 Jan 242018 Jan 27

Other

Other17th International Conference on Electronics, Information and Communication, ICEIC 2018
Country/TerritoryUnited States
CityHonolulu
Period18/1/2418/1/27

Keywords

  • Anomaly detection
  • Healthcare
  • Hidden Markov Model
  • Sensor network

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications
  • Computer Science Applications
  • Signal Processing
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Method of behavior modeling for detection of anomaly behavior using hidden Markov model'. Together they form a unique fingerprint.

Cite this