Doppler Analysis Based Fall Detection Using Array Antenna

Yugo Agata, Tomoaki Ohtsuki, Kentaro Toyoda

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

3 Citations (Scopus)

Abstract

The number of elderly people who live alone is increasing in many countries. Furthermore, many of their accidents occur at home. Hence, it is an urgent demand for a system monitoring their activities to detect accidents indoor such as falling. In conventional systems of fall detection using array antennas, falling after standing still can be detected with high accuracy by leveraging the features indicating the change of radio wave propagation. However, it is difficult to detect falling after walking correctly. In this paper, to improve fall detection accuracy including falling after walking, we propose an accurate fall detection system by leveraging the features indicating the change of Doppler signals during human activities in detail. Analyzing Doppler signals is useful to detect falling since they are observed when a radio wave reflects by moving objects. We conducted experiments in actual rooms to demonstrate that the proposed method can detect falling after both standing and walking with high accuracy.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Communications, ICC 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Volume2018-May
ISBN (Print)9781538631805
DOIs
Publication statusPublished - 2018 Jul 27
Event2018 IEEE International Conference on Communications, ICC 2018 - Kansas City, United States
Duration: 2018 May 202018 May 24

Other

Other2018 IEEE International Conference on Communications, ICC 2018
Country/TerritoryUnited States
CityKansas City
Period18/5/2018/5/24

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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