Non-Contact Detection of Vital Signs with a Hybrid Feature Extraction Method using a UWB Radar Sensor

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

3 Scopus Citations
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Author(s)

  • Jiajian Zhu
  • Jin Li
  • Haizhu Xie
  • Lixin Wang

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publication2021 IEEE 6th International Conference on Intelligent Computing and Signal Processing (ICSP)
PublisherInstitute of Electrical and Electronics Engineers, Inc.
Pages1140-1144
ISBN (electronic)9780738143705, 9780738143699
ISBN (print)9781665404136
Publication statusPublished - Apr 2021

Publication series

NameIEEE International Conference on Intelligent Computing and Signal Processing, ICSP

Conference

Title6th IEEE International Conference on Intelligent Computing and Signal Processing (ICSP 2021)
PlaceChina
CityXi'an
Period9 - 11 April 2021

Link(s)

DOI

DOI
Check@CityULib
Link to Scopus https://www.scopus.com/record/display.uri?eid=2-s2.0-85105508069&origin=recordpage
Permanent Link https://scholars.cityu.edu.hk/en/publications/publication(56190d20-b87e-4ec3-9524-46c6b5e9e0f7).html

Abstract

The ultra-wide band (UWB) radar sensor is widely used in Radar-based Life Detecting System for search and rescue due to its short detection time, high penetrating power and low energy consumption. However, performance of non-contact detection is limited in complex post-disaster environments due to the noise and clutter. In this paper, a hybrid feature extraction method based on Hilbert-Huang Transform (HHT), Fast Fourier Transform (FFT) and correlation analysis is proposed to obtain the echo signal features. Then a classification model based on support vector machine (SVM) is established to identify the respiratory information embedded in the echo signal. The experimental results show that the proposed method can accurately identify the location of human body through different obstacles.

Research Area(s)

  • hybrid feature extraction, life detection, SVM, UWB radar

Fingerprint

Publication fingerprints text

100
Feature Extraction Engineering
100
Ultra Wide Band Engineering
100
Vital Sign Engineering
100
Radar Sensor Engineering
100
Detection Engineering
100
Hybrid Engineering
100
Isolation Method Engineering
100
detection INIS
100
extraction INIS
100
hybrids INIS
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Citation Format(s)

[ RIS ] [ BibTeX ]
Non-Contact Detection of Vital Signs with a Hybrid Feature Extraction Method using a UWB Radar Sensor. / Zhu, Jiajian; Li, Jin; Fan, Zhening et al.
2021 IEEE 6th International Conference on Intelligent Computing and Signal Processing (ICSP). Institute of Electrical and Electronics Engineers, Inc., 2021. p. 1140-1144 9408726 (IEEE International Conference on Intelligent Computing and Signal Processing, ICSP).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review