IPrevent: A novel wearable radio frequency range detector for fall prevention

Yao Tang, Zhengyu Peng, Lixin Ran, Changzhi Li

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

6 Scopus citations

Abstract

Falling is a serious and costly health problem for senior people. It is reported that one out of three senior people around the world falls every year. As a result, a large number of fall detection and fall prevention systems are developed. In existing technologies, camera-based and inertial measurement unit-based are two dominant methods for fall prevention. Considerable radar-based researches were carried out as well, however, most of them were focused on fall detection. Therefore, this paper presents a theoretical study on a novel all-time fall prevention system using on-shoe K-band frequency-modulaed continuous-wave(FMCW) radar, which is capable of detecting the absolute distance between the radar and the obstacles in front of the shoe. The concept of fall prevention is illustrated, and a FMCW radar prototype is tested to demonstrate the feasibility of radio frequency range detector for fall prevention.

Original languageEnglish
Title of host publicationRFIT 2016 - 2016 IEEE International Symposium on Radio-Frequency Integration Technology
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509012350
DOIs
StatePublished - Sep 27 2016
Event2016 IEEE International Symposium on Radio-Frequency Integration Technology, RFIT 2016 - Taipei, Taiwan, Province of China
Duration: Aug 24 2016Aug 26 2016

Publication series

NameRFIT 2016 - 2016 IEEE International Symposium on Radio-Frequency Integration Technology

Conference

Conference2016 IEEE International Symposium on Radio-Frequency Integration Technology, RFIT 2016
Country/TerritoryTaiwan, Province of China
CityTaipei
Period08/24/1608/26/16

Fingerprint

Dive into the research topics of 'IPrevent: A novel wearable radio frequency range detector for fall prevention'. Together they form a unique fingerprint.

Cite this