Doppler Analysis Based Fall Detection Using Array Antenna

Yugo Agata, Tomoaki Ohtsuki, Kentaro Toyoda

研究成果: Conference contribution

3 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトル2018 IEEE International Conference on Communications, ICC 2018 - Proceedings
出版社Institute of Electrical and Electronics Engineers Inc.
2018-May
ISBN(印刷版)9781538631805
DOI
出版ステータスPublished - 2018 7月 27
イベント2018 IEEE International Conference on Communications, ICC 2018 - Kansas City, United States
継続期間: 2018 5月 202018 5月 24

Other

Other2018 IEEE International Conference on Communications, ICC 2018
国/地域United States
CityKansas City
Period18/5/2018/5/24

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信
  • 電子工学および電気工学

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