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

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 s...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Ročník 2018; s. 1 - 6
Hlavní autoři: Ye, Chen, Toyoda, Kentaroh, Ohtsuki, Tomoaki
Médium: Konferenční příspěvek Journal Article
Jazyk:angličtina
japonština
Vydáno: United States IEEE 01.07.2018
Témata:
ISSN:1557-170X, 2694-0604, 1558-4615, 2694-0604
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
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.
AbstractList 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.
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.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.
Author Ye, Chen
Toyoda, Kentaroh
Ohtsuki, Tomoaki
Author_xml – sequence: 1
  givenname: Chen
  surname: Ye
  fullname: Ye, Chen
  email: yechen@ohtsuki.ics.keio.ac.jp
  organization: School of Science and Technology, Keio University, Yokohama, 223-8522, Japan
– sequence: 2
  givenname: Kentaroh
  surname: Toyoda
  fullname: Toyoda, Kentaroh
  email: toyoda@ohtsuki.ics.keio.ac.jp
  organization: Department of Information and Computer Science, Keio University, Yokohama, 223-8522, Japan
– sequence: 3
  givenname: Tomoaki
  surname: Ohtsuki
  fullname: Ohtsuki, Tomoaki
  email: ohtsuki@ics.keio.ac.jp
  organization: School of Science and Technology, Keio University, Yokohama, 223-8522, Japan
BackLink https://www.ncbi.nlm.nih.gov/pubmed/30440259$$D View this record in MEDLINE/PubMed
BookMark eNo9kUlvGzEMhdUiRbP-gKJAoWMu44haZjRH11mBpD3UWW6GpOEkKjySK8kO-u8zSJyc-MD3gQQf98lOiAEJ-QZsAsDak7Obn7MJZ6AnWgFXUn4iR22jQQldi1rW9WeyB0rpStagdl51U0HDHnbJfs5_GeOMKfhKdgWTknHV7pHN1bBKcYMd_bMyKSOddmZV_GYUy8eYfHkaMu1jolPn1skUpL9iqFwMxbhCL9GkYtEUeooFXfEx0NvswyOd-wGrex-6-FzdmeTNqzdH9xT8vzUeki-9WWY82tYDcnt-Np9dVte_L65m0-vKcwmlEl1t0DKnnAWp2qYHaHuw0AgtrO16hZKNx-uucRzbsQfK9q1FbpnlRnfigBy_zR2PHNfmshh8drhcmoBxnRccxJikbhkb0R9bdG0H7Bar5AeT_i_esxqB72-AR8QPe_sJ8QICaXrz
ContentType Conference Proceeding
Journal Article
DBID 6IE
6IH
CBEJK
RIE
RIO
NPM
7X8
DOI 10.1109/EMBC.2018.8512544
DatabaseName IEEE Electronic Library (IEL) Conference Proceedings
IEEE Proceedings Order Plan (POP) 1998-present by volume
IEEE Xplore All Conference Proceedings
IEEE Electronic Library (IEL)
IEEE Proceedings Order Plans (POP) 1998-present
PubMed
MEDLINE - Academic
DatabaseTitle PubMed
MEDLINE - Academic
DatabaseTitleList PubMed
MEDLINE - Academic

Database_xml – sequence: 1
  dbid: NPM
  name: PubMed
  url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed
  sourceTypes: Index Database
– sequence: 2
  dbid: RIE
  name: IEEE Electronic Library (IEL)
  url: https://ieeexplore.ieee.org/
  sourceTypes: Publisher
– sequence: 3
  dbid: 7X8
  name: MEDLINE - Academic
  url: https://search.proquest.com/medline
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
EISBN 9781538636466
1538636468
EISSN 1558-4615
2694-0604
EndPage 6
ExternalDocumentID 30440259
8512544
Genre orig-research
Journal Article
GroupedDBID 6IE
6IF
6IH
AAJGR
ACGFS
AFFNX
ALMA_UNASSIGNED_HOLDINGS
CBEJK
M43
RIE
RIO
RNS
29F
29G
6IK
6IM
IPLJI
NPM
7X8
ID FETCH-LOGICAL-i241t-3d6aeb0c5cb14597f119f1b17383bbdf5e405388d7c2e983b15bf9be2b0b2a8d3
IEDL.DBID RIE
ISSN 1557-170X
2694-0604
IngestDate Sun Nov 09 10:00:23 EST 2025
Mon Jul 21 06:18:13 EDT 2025
Wed Aug 27 02:50:00 EDT 2025
IsPeerReviewed true
IsScholarly true
Language English
Japanese
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i241t-3d6aeb0c5cb14597f119f1b17383bbdf5e405388d7c2e983b15bf9be2b0b2a8d3
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
PMID 30440259
PQID 2135128900
PQPubID 23479
PageCount 6
ParticipantIDs pubmed_primary_30440259
proquest_miscellaneous_2135128900
ieee_primary_8512544
PublicationCentury 2000
PublicationDate 2018-07-00
PublicationDateYYYYMMDD 2018-07-01
PublicationDate_xml – month: 07
  year: 2018
  text: 2018-07-00
PublicationDecade 2010
PublicationPlace United States
PublicationPlace_xml – name: United States
PublicationTitle Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
PublicationTitleAbbrev EMBC
PublicationTitleAlternate Conf Proc IEEE Eng Med Biol Soc
PublicationYear 2018
Publisher IEEE
Publisher_xml – name: IEEE
SSID ssj0020051
ssj0061641
ssib061542107
ssib053545923
ssib042469959
Score 2.1581047
Snippet Recently, a sparse adaptive algorithm termed zero-attracting sign least-mean-square (ZA-SLMS), has been clarified to be able to reconstruct robustly heartbeat...
SourceID proquest
pubmed
ieee
SourceType Aggregation Database
Index Database
Publisher
StartPage 1
SubjectTerms Adaptive algorithms
Doppler radar
Estimation
Heart beat
Heart rate variability
Title Improved Sparse Adaptive Algorithms for Accurate Non-contact Heartbeat Detection Using Time-Window-Variation Technique
URI https://ieeexplore.ieee.org/document/8512544
https://www.ncbi.nlm.nih.gov/pubmed/30440259
https://www.proquest.com/docview/2135128900
Volume 2018
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3JTsMwEB0VxAEubAXKJiNxJBBnqeNj2dQDVEhsvVVeJlAJkqpN4ffxJGnhAAduUSRHkWc0nud58wbgWPhpSEJoXpBi7EU2ki4OhkQT41paGSuuSp3ZG9HrJf2-vGvAybwXBhFL8hme0mNZy7e5mdJV2ZnLDkhRawEWhGhXvVpzcEXeVVctuS_Prm7PL4i4lZzWi-rpKX8nkuWBcr36v19Zg-Z3Zx67m58569DAbANWfogKbsJHdU-Alt2PHGpF1rFqREGNdd5e8vGweH2fMJeqso4xUxKKYL0884iyrkzBus7zC-0CNLvEoqRpZaykFTBqFvGeHYTPP70nh7BLk7KHmQZsEx6vrx4uul49XcEbulO78ELbVqh9ExvNIwcrUs5lyjUXDrNqbdMYXS4XJokVJkDp3vFYp1JjoH0dqMSGW7CY5RnuALOpMGnYjiMTywhFW4vARMpIg4FJUKsWbNIODkaVgMag3rwWHM1sMXBOTZUKlWE-nQwCmhtIJVC_BduVkeaLQxqS7UDb7u8f3YNlMnvFqN2HxWI8xQNYMh_FcDI-dJ7TTw5Lz_kCIL3FgA
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3JTsNADLXYJODCDmUdJI6EZrI0mWPZVESpkCjLLZrFgUqQVG0Kv884DYUDHLhFkSaKZizbb_z8DHAUualPQmiOl2LoBCYQ1g_6RBPjShgRSi5Lndl21OnET0_idgqOJ70wiFiSz_CEHstavsn1iK7K6jY7IEWtaZilyVlVt9YEXpF9VXVL7or6xc3pGVG34pNqWTU_5e9Usgwpl0v_-5llWP_uzWO3k6izAlOYrcLiD1nBNXgf3xSgYXd9i1uRNY3sk1tjzdfnfNArXt6GzCarrKn1iKQiWCfPHCKtS12wlrX9QlkXzc6xKIlaGSuJBYzaRZxHC-LzD-fBYuzyUFn3SwV2He4vL7pnLaear-D0bNwuHN80JCpXh1rxwAKLlHORcsUji1qVMmmINpvz49hE2kNh3_FQpUKhp1zlydj4GzCT5RluATNppFO_EQY6FAFGDRV5OpBaaPR0jErWYI12MOmPJTSSavNqcPh1Fok1a6pVyAzz0TDxaHIgFUHdGmyOD2my2Kcx2Ra2bf_-0QOYb3Vv2kn7qnO9AwtkAmN-7S7MFIMR7sGcfi96w8F-aT-f5MzH4Q
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=Proceedings+of+the+annual+international+conference+of+the+IEEE+Engineering+in+Medicine+and+Biology+Society&rft.atitle=Improved+Sparse+Adaptive+Algorithms+for+Accurate+Non-contact+Heartbeat+Detection+Using+Time-Window-Variation+Technique&rft.au=Ye%2C+Chen&rft.au=Toyoda%2C+Kentaroh&rft.au=Ohtsuki%2C+Tomoaki&rft.date=2018-07-01&rft.pub=IEEE&rft.eissn=1558-4615&rft.spage=1&rft.epage=6&rft_id=info:doi/10.1109%2FEMBC.2018.8512544&rft.externalDocID=8512544
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1557-170X&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1557-170X&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1557-170X&client=summon