Computer Science ›› 2020, Vol. 47 ›› Issue (10): 48-54.doi: 10.11896/jsjkx.200500057

Special Issue: Mobile Crowd Sensing and Computing

• Mobile Crowd Sensing and Computing • Previous Articles     Next Articles

Vital Signs Monitoring Method Based on Channel State Phase Information

DAI Huan1,2, JIANG Jing-jing1, SHU Qin-dong 1, SHI Peng-zhan1, SHI Wen-hua1   

  1. 1 School of Electronic and Information Engineering,Suzhou University of Science and Technology,Suzhou,Jiangsu 215000,China
    2 School of Computer Science and Techonology,Soochow University,Suzhou,Jiangsu 215000,China
  • Received:2020-05-14 Revised:2020-08-20 Online:2020-10-15 Published:2020-10-16
  • About author:DAI Huan,born in 1983,Ph.D,associate professor,is a member of China Computer Federation.His main research interests include localization,internet of things and information processing.
  • Supported by:
    National Natural Science Foundation of China (61702354,61876121), Scientific Research Project of Suzhou University of Science and Technology(XKZ2017004), Key Laboratory of Mobile Interconnection Technology Engineering of Jiangsu Province(JSWLW2017004) and Graduate Research Innovation Project (SKSJ18_012,SJCX19_0963)

Abstract: With the development of wireless communication technology,wireless sensing technology has been widely studied.This paper proposes vital signs monitoring method based on CSI phase.The method employs commodity WiFi to obtain CSI phase information.The liner transformation is used to reduce phase shift and delay interference caused by un-synchronization of transmitter and receiver.Hampel filter is implemented to filter out DC component and high frequency noises influenced by signal fading and multipath effects.Discrete wavelet transform is utilized to realize vital signs extraction.According to the characterizes of breathing and heartbeat frequency,multi-subcarrier fusion and Fast Fourier Transform algorithms are respectively employed to estimate breathing and heart rates.Experimental results show that the method can effectively capture vital signs in multiple scenarios.

Key words: Channel state phase information, Detail coefficient, Frequency estimation, Vital signs

CLC Number: 

  • TP309.1
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