Improved Sparse Adaptive Algorithms for Accurate Non-contact Heartbeat Detection Using Time-Window-Variation Technique

Chen Ye, Kentaro Toyoda, Tomoaki Ohtsuki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Recently, a sparse adaptive algorithm termed zero-attracting sign least-mean-square (ZA-SLMS), has been clarified to be able to reconstruct robustly heartbeat spectrum by Doppler radar signal. However, since the strengths of noise evidently differ under different body motions, the sparse heartbeat spectra cannot be always acquired accurately by the constant regularization parameter (REPA) that balances the gradient correction and the sparse penalty, applying in the ZA-SLMS algorithm. In this paper, an improved ZA-SLMS algorithm is proposed by introducing adaptive REPA (AREPA), where the proportion of sparse penalty is adjusted based on the standard deviation of radar data. Moreover, to enhance the stability of heartbeat detection, a time-window-variation (TWV) technique is further introduced in the improved ZA-SLMS algorithm, considering the fact that the position of spectral peak associated with the heart rate (HR) is stable when the length of time window changes within a short period. Experimental results measured against five subjects validated that our proposal reliably improves the error of HR estimation than the standard ZA-SLMS algorithm.

Original languageEnglish
Title of host publication40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
Volume2018-July
ISBN (Electronic)9781538636466
DOIs
Publication statusPublished - 2018 Oct 26
Event40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 - Honolulu, United States
Duration: 2018 Jul 182018 Jul 21

Other

Other40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
CountryUnited States
CityHonolulu
Period18/7/1818/7/21

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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    Ye, C., Toyoda, K., & Ohtsuki, T. (2018). Improved Sparse Adaptive Algorithms for Accurate Non-contact Heartbeat Detection Using Time-Window-Variation Technique. In 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 (Vol. 2018-July, pp. 1-6). [8512544] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2018.8512544