TagFall: towards unobstructive fine-grained fall detection based on uhf passive RFID tags

Wenjie Ruan, Lina Yao, Quan Z. Sheng, Nickolas J. G. Falkner, Xue Li, Tao Gu

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

Abstract

Falls are among the leading causes of hospitalization for the elderly and illness individuals. Considering that the elderly often live alone and receive only irregular visits, it is essential to develop such a system that can effectively detect a fall or abnormal activities. However, previous fall detection systems either require to wear sensors or are able to detect a fall but fail to provide fine-grained contextual information (e.g., what is the person doing before falling, falling directions). In this paper, we propose a device-free, fine-grained fall detection system based on pure passive UHF RFID tags, which not only is capable of sensing regular actions and fall events simultaneously, but also provide caregivers the contexts of fall orientations. We first augment the Angle-based Outlier Detection Method (ABOD) to classify normal actions (e.g., standing, sitting, lying and walking) and detect a fall event. Once a fall event is detected, we first segment a fix-length RSSI data stream generated by the fall and then utilize Dynamic Time Warping (DTW) based kNN to distinguish the falling direction. The experimental results demonstrate that our proposed approach can distinguish the living status before fall happening, as well as the fall orientations with a high accuracy. The experiments also show that our device-free, fine-grained fall detection system offers a good overall performance and has the potential to better support the assisted living of older people.

Original languageEnglish
Title of host publicationProceedings of the 12th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous 2015)
EditorsPei Zhang, Jorge Sá Silva, Nic Lane, Fernando Boavida, André Rodrigues
Place of PublicationBrussels, Belgium
PublisherICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering)
Number of pages10
ISBN (Print)9781631900723
DOIs
Publication statusPublished - 2015
Externally publishedYes
Event12th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MOBIQUITOUS 2015 - Coimbra, Portugal
Duration: 22 Jul 201524 Jul 2015

Other

Other12th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MOBIQUITOUS 2015
CountryPortugal
CityCoimbra
Period22/07/1524/07/15

Bibliographical note

Copyright the Author(s) 2015. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

  • Fall Detection
  • Device-Free
  • RFID
  • Anomaly Detection
  • Household Monitoring

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