Multi-breath: Separate respiration monitoring for multiple persons with UWB radar

Yanni Yang, Jiannong Cao, Xiulong Liu, Xuefeng Liu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

14 Citations (Scopus)

Abstract

Human respiration state is an important indicator to reflect health conditions. Recent advances in wireless human sensing have enabled device-free respiration monitoring using narrow-band wireless signals, which, however, fail to map the estimated respiration states to multiple persons. In this paper, we present Multi-Breath, a UWB-based system to achieve separate respiration monitoring for multiple persons. The UWB radar can accurately measure the travelling distance of the signals, which helps to separate the signals affected by different persons and map the detected respiration patterns to the corresponding persons with the location information. However, the radar signal time series of each person are quite noisy due to the multi-path effects caused by the respiration movements of other persons, making it difficult to accurately estimate the respiration state. To overcome this challenge, we propose to transform the UWB radar signal matrices of different persons as separate RGB images to reveal the respiration pattern of each individual. Then, the image processing operations, including image smoothing, edge detection, dilation and erosion, are applied to identify the breathing cycles. Finally, the respiration state, including the respiration rate and the presence of apnea, is estimated via blob detection and calibration. Extensive experiments show that the mean absolute error on respiration rate estimation is 0.3-0.6 bpm, and the percentage of missed and false detected apnea is 3%-7%.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE 43rd Annual Computer Software and Applications Conference, COMPSAC 2019
EditorsVladimir Getov, Jean-Luc Gaudiot, Nariyoshi Yamai, Stelvio Cimato, Morris Chang, Yuuichi Teranishi, Ji-Jiang Yang, Hong Va Leong, Hossian Shahriar, Michiharu Takemoto, Dave Towey, Hiroki Takakura, Atilla Elci, Susumu Takeuchi, Satish Puri
PublisherIEEE Computer Society
Pages840-849
Number of pages10
ISBN (Electronic)9781728126074
DOIs
Publication statusPublished - Jul 2019
Event43rd IEEE Annual Computer Software and Applications Conference, COMPSAC 2019 - Milwaukee, United States
Duration: 15 Jul 201919 Jul 2019

Publication series

NameProceedings - International Computer Software and Applications Conference
Volume1
ISSN (Print)0730-3157

Conference

Conference43rd IEEE Annual Computer Software and Applications Conference, COMPSAC 2019
Country/TerritoryUnited States
CityMilwaukee
Period15/07/1919/07/19

Keywords

  • Apnea Detection
  • Multiple Persons
  • Respiration Rate Estimation
  • UWB Radar

ASJC Scopus subject areas

  • Software
  • Computer Science Applications

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