UWB Simultaneous Breathing and Heart Rate Detections in Driving Scenario Using Multi-Feature Alignment Two-Layer EEMD Method

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9 Scopus citations

Abstract

Remote sensing of life detection or a non-contact monitor of vital signals is an important application for Ultra-wideband (UWB) radar, such as health monitoring of a vehicle driver. Using the UWB radar to detect physiological signals of a dynamic human, three kind movement features (body motion, breathing, and heartbeat) must be considered generally to be extracted from echo pulses. Usually, moving body echo signal is much larger than other twos, which will cause signal interference and interaction problems. Meanwhile, since moving body causes breathing and heartbeat to act in dynamic spatial position, conventional fixed feature with maximum spectrum or local peak spectrum detection methods are not likely to find those movable physiological active features. Thus, how to reduce physiological feature bias from body motion, and efficiently obtain valuable physiological information are problems. To solve these problems, a novel multi-feature alignment (MFA) two-layer EEMD method is proposed. The proposed method simultaneously detects breathing and heartbeat information from a slightly swinging human (driver). The simulation and experiment results show the proposed method can effectively and reliably evaluate breathing and heart rates in static or/and dynamic body situation, both in laboratory and car.

Original languageEnglish
Article number9086782
Pages (from-to)10251-10266
Number of pages16
JournalIEEE Sensors Journal
Volume20
Issue number17
DOIs
StatePublished - 1 Sep 2020

Keywords

  • Alignment
  • breathing rate
  • driver
  • ensemble empirical mode decomposition (EEMD)
  • heart rate
  • intrinsic mode function (IMF)
  • remote sensing
  • tracking
  • ultra-wideband (UWB) radar

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