Interference motion removal for Doppler radar vital sign detection using variational encoder-decoder neural network

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Abstract

A novel approach to the removal of interference motions through the use of a variational encoder-decoder convolutional neural network is presented for Doppler radar vital sign detection. The approach is evaluated on semi-experimental data containing real vital sign signatures and simulated returns from interfering body motions. It is further demonstrated that the model can enhance the extraction of the micro-Doppler frequency corresponding to the respiration rate.
Original languageEnglish
Number of pages6
Publication statusPublished - 14 May 2021
Event2021 IEEE Radar Conference - Virtual/Atlanta, GA, USA, Atlanta, United States
Duration: 10 May 202114 May 2021
https://ewh.ieee.org/conf/radar/2021/

Conference

Conference2021 IEEE Radar Conference
Abbreviated titleRadarConf 2021
CountryUnited States
CityAtlanta
Period10/05/2114/05/21
Internet address

Keywords

  • Doppler radar
  • heart rate monitoring
  • respiration rate monitoring
  • vital signs
  • random body movement
  • variational autoencoder

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