Detecting unexpected fall using array antenna

Yusuke Hino, Jihoon Hong, Tomoaki Ohtsuki

研究成果: Conference contribution

3 被引用数 (Scopus)

抄録

Nowadays, the population of the elderly people is increasing in Japan. The system to protect an elderly person who is living alone is needful. The bigger part of the accident in their house is falling. There are several kinds of products to detect a person's fall. However, there are some problems that it does not have enough detection range and privacy. Array antenna is an antenna, which detects radio wave propagation by observing the direction of arrival (DOA) of the signal. We developed previously the fall detection using array antenna. In the conventional fall detection method, it is needed to learn and observe the whole activity scenario, which includes how the person moves before and after the fall. As a result, when the unexpected fall scenario happens, it is not able to detect the fall correctly. In this paper, we propose a detection algorithm for unexpected fall using array antenna. We detect fall for every fixed time, and by the results of the detection, we decide whether the activity is falling or not. By using this method, it can detect the unexpected fall scenario, which is not learned. In addition, we use new features for support vector machine (SVM) to distinguish confusing activities and improve the fall detection accuracy.

本文言語English
ホスト出版物のタイトルIEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
出版社Institute of Electrical and Electronics Engineers Inc.
ページ2104-2108
ページ数5
2015-June
ISBN(印刷版)9781479949120
DOI
出版ステータスPublished - 2015 6 25
イベント2014 25th IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communication, IEEE PIMRC 2014 - Washington, United States
継続期間: 2014 9 22014 9 5

Other

Other2014 25th IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communication, IEEE PIMRC 2014
国/地域United States
CityWashington
Period14/9/214/9/5

ASJC Scopus subject areas

  • 電子工学および電気工学

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