PCA-Based Multi-Wavelength Photoplethysmography Algorithm for Cuffless Blood Pressure Measurement on Elderly Subjects

The prevalence of hypertension has made blood pressure (BP) measurement one of the most wanted functions in wearable devices for convenient and frequent self-assessment of health conditions. The widely adopted principle for cuffless BP monitoring is based on arterial pulse transit time (PTT), which...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE journal of biomedical and health informatics Jg. 25; H. 3; S. 663 - 673
Hauptverfasser:	Liu, Jing, Qiu, Shirong, Luo, Ningqi, Lau, Sze-Kei, Yu, Hui, Kwok, Timothy, Zhang, Yuan-Ting, Zhao, Ni
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.03.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Biomedical monitoring Blood Blood pressure cuffless blood pressure measurement EKG Electrocardiography Hypertension Lag time Medical equipment multi-wavelength photoplethysmography Older people Pressure measurement Principal component analysis Principal components analysis Reactive power Self-assessment Sensors Skin Statistical analysis Telemedicine Transit time Waveforms Wavelength Wearable technology
ISSN:	2168-2194, 2168-2208, 2168-2208
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Abstract	The prevalence of hypertension has made blood pressure (BP) measurement one of the most wanted functions in wearable devices for convenient and frequent self-assessment of health conditions. The widely adopted principle for cuffless BP monitoring is based on arterial pulse transit time (PTT), which is measured with electrocardiography and photoplethysmography (PPG). To achieve cuffless BP monitoring with more compact wearable electronics, we have previously conceived a multi-wavelength PPG (MWPPG) strategy to perform BP estimation from arteriolar PTT, requiring only a single sensing node. However, challenges remain in decoding the compounded MWPPG signals consisting of both heterogeneous physiological information and motion artifact (MA). In this work, we proposed an improved MWPPG algorithm based on principal component analysis (PCA) which matches the statistical decomposition results with the arterial pulse and capillary pulse. The arteriolar PTT is calculated accordingly as the phase shift based on the entire waveforms, instead of local peak lag time, to enhance the feature robustness. Meanwhile, the PCA-derived MA component is employed to identify and exclude the MA-contaminated segments. To evaluate the new algorithm, we performed a comparative experiment (N = 22) with a cuffless MWPPG measurement device and used double-tube auscultatory BP measurement as a reference. The results demonstrate the accuracy improvement enabled by the PCA-based operations on MWPPG signals, yielding errors of 1.44 ± 6.89 mmHg for systolic blood pressure and −1.00 ± 6.71 mm Hg for diastolic blood pressure. In conclusion, the proposed PCA-based method can improve the performance of MWPPG in wearable medical devices for cuffless BP measurement.
AbstractList	The prevalence of hypertension has made blood pressure (BP) measurement one of the most wanted functions in wearable devices for convenient and frequent self-assessment of health conditions. The widely adopted principle for cuffless BP monitoring is based on arterial pulse transit time (PTT), which is measured with electrocardiography and photoplethysmography (PPG). To achieve cuffless BP monitoring with more compact wearable electronics, we have previously conceived a multi-wavelength PPG (MWPPG) strategy to perform BP estimation from arteriolar PTT, requiring only a single sensing node. However, challenges remain in decoding the compounded MWPPG signals consisting of both heterogeneous physiological information and motion artifact (MA). In this work, we proposed an improved MWPPG algorithm based on principal component analysis (PCA) which matches the statistical decomposition results with the arterial pulse and capillary pulse. The arteriolar PTT is calculated accordingly as the phase shift based on the entire waveforms, instead of local peak lag time, to enhance the feature robustness. Meanwhile, the PCA-derived MA component is employed to identify and exclude the MA-contaminated segments. To evaluate the new algorithm, we performed a comparative experiment (N = 22) with a cuffless MWPPG measurement device and used double-tube auscultatory BP measurement as a reference. The results demonstrate the accuracy improvement enabled by the PCA-based operations on MWPPG signals, yielding errors of 1.44 ± 6.89 mmHg for systolic blood pressure and −1.00 ± 6.71 mm Hg for diastolic blood pressure. In conclusion, the proposed PCA-based method can improve the performance of MWPPG in wearable medical devices for cuffless BP measurement. The prevalence of hypertension has made blood pressure (BP) measurement one of the most wanted functions in wearable devices for convenient and frequent self-assessment of health conditions. The widely adopted principle for cuffless BP monitoring is based on arterial pulse transit time (PTT), which is measured with electrocardiography and photoplethysmography (PPG). To achieve cuffless BP monitoring with more compact wearable electronics, we have previously conceived a multi-wavelength PPG (MWPPG) strategy to perform BP estimation from arteriolar PTT, requiring only a single sensing node. However, challenges remain in decoding the compounded MWPPG signals consisting of both heterogeneous physiological information and motion artifact (MA). In this work, we proposed an improved MWPPG algorithm based on principal component analysis (PCA) which matches the statistical decomposition results with the arterial pulse and capillary pulse. The arteriolar PTT is calculated accordingly as the phase shift based on the entire waveforms, instead of local peak lag time, to enhance the feature robustness. Meanwhile, the PCA-derived MA component is employed to identify and exclude the MA-contaminated segments. To evaluate the new algorithm, we performed a comparative experiment (N = 22) with a cuffless MWPPG measurement device and used double-tube auscultatory BP measurement as a reference. The results demonstrate the accuracy improvement enabled by the PCA-based operations on MWPPG signals, yielding errors of 1.44 ± 6.89 mmHg for systolic blood pressure and -1.00 ± 6.71 mm Hg for diastolic blood pressure. In conclusion, the proposed PCA-based method can improve the performance of MWPPG in wearable medical devices for cuffless BP measurement. The prevalence of hypertension has made blood pressure (BP) measurement one of the most wanted functions in wearable devices for convenient and frequent self-assessment of health conditions. The widely adopted principle for cuffless BP monitoring is based on arterial pulse transit time (PTT), which is measured with electrocardiography and photoplethysmography (PPG). To achieve cuffless BP monitoring with more compact wearable electronics, we have previously conceived a multi-wavelength PPG (MWPPG) strategy to perform BP estimation from arteriolar PTT, requiring only a single sensing node. However, challenges remain in decoding the compounded MWPPG signals consisting of both heterogeneous physiological information and motion artifact (MA). In this work, we proposed an improved MWPPG algorithm based on principal component analysis (PCA) which matches the statistical decomposition results with the arterial pulse and capillary pulse. The arteriolar PTT is calculated accordingly as the phase shift based on the entire waveforms, instead of local peak lag time, to enhance the feature robustness. Meanwhile, the PCA-derived MA component is employed to identify and exclude the MA-contaminated segments. To evaluate the new algorithm, we performed a comparative experiment (N = 22) with a cuffless MWPPG measurement device and used double-tube auscultatory BP measurement as a reference. The results demonstrate the accuracy improvement enabled by the PCA-based operations on MWPPG signals, yielding errors of 1.44 ± 6.89 mmHg for systolic blood pressure and -1.00 ± 6.71 mm Hg for diastolic blood pressure. In conclusion, the proposed PCA-based method can improve the performance of MWPPG in wearable medical devices for cuffless BP measurement.The prevalence of hypertension has made blood pressure (BP) measurement one of the most wanted functions in wearable devices for convenient and frequent self-assessment of health conditions. The widely adopted principle for cuffless BP monitoring is based on arterial pulse transit time (PTT), which is measured with electrocardiography and photoplethysmography (PPG). To achieve cuffless BP monitoring with more compact wearable electronics, we have previously conceived a multi-wavelength PPG (MWPPG) strategy to perform BP estimation from arteriolar PTT, requiring only a single sensing node. However, challenges remain in decoding the compounded MWPPG signals consisting of both heterogeneous physiological information and motion artifact (MA). In this work, we proposed an improved MWPPG algorithm based on principal component analysis (PCA) which matches the statistical decomposition results with the arterial pulse and capillary pulse. The arteriolar PTT is calculated accordingly as the phase shift based on the entire waveforms, instead of local peak lag time, to enhance the feature robustness. Meanwhile, the PCA-derived MA component is employed to identify and exclude the MA-contaminated segments. To evaluate the new algorithm, we performed a comparative experiment (N = 22) with a cuffless MWPPG measurement device and used double-tube auscultatory BP measurement as a reference. The results demonstrate the accuracy improvement enabled by the PCA-based operations on MWPPG signals, yielding errors of 1.44 ± 6.89 mmHg for systolic blood pressure and -1.00 ± 6.71 mm Hg for diastolic blood pressure. In conclusion, the proposed PCA-based method can improve the performance of MWPPG in wearable medical devices for cuffless BP measurement.
Author	Yu, Hui Zhao, Ni Liu, Jing Luo, Ningqi Kwok, Timothy Lau, Sze-Kei Zhang, Yuan-Ting Qiu, Shirong
Author_xml	– sequence: 1 givenname: Jing orcidid: 0000-0003-3088-1673 surname: Liu fullname: Liu, Jing email: 93liujing@gmail.com organization: Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China – sequence: 2 givenname: Shirong surname: Qiu fullname: Qiu, Shirong email: srqiu@link.cuhk.edu.hk organization: Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China – sequence: 3 givenname: Ningqi surname: Luo fullname: Luo, Ningqi email: nqluo@cuhk.edu.hk organization: Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China – sequence: 4 givenname: Sze-Kei surname: Lau fullname: Lau, Sze-Kei email: jessicalau@cuhk.edu.hk organization: Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China – sequence: 5 givenname: Hui surname: Yu fullname: Yu, Hui email: yuhui861202@gmail.com organization: Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China – sequence: 6 givenname: Timothy surname: Kwok fullname: Kwok, Timothy email: tkwok@cuhk.edu.hk organization: Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China – sequence: 7 givenname: Yuan-Ting orcidid: 0000-0003-4150-5470 surname: Zhang fullname: Zhang, Yuan-Ting email: yt.zhang@cityu.edu.hk organization: Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China – sequence: 8 givenname: Ni orcidid: 0000-0002-1536-8516 surname: Zhao fullname: Zhao, Ni email: nzhao@cuhk.edu.hk organization: Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/32750946$$D View this record in MEDLINE/PubMed
BookMark	eNp9kcFq3DAQhkVJadI0D1AKRdBLLt5Ksi1Lx90laVISutCWHoUsj9deZGsryYV9-8rsbg85dC4zDN8_zMz_Fl2MbgSE3lOyoJTIz19XD48LRhhZ5IQUJGev0BWjXGSMEXFxrqksLtFNCDuSQqSW5G_QZc6qksiCX6Fps15mKx2gwc-TjX32S_8BC-M2dnjTuej2FmJ3CIPber3vDnhpt873sRtw6zxeT21rIQS8ss41eONTPXnAz6DnPMAYsRvxnW3A2wP-PtU7MDG8Q69bbQPcnPI1-nl_92P9kD19-_K4Xj5lpqBlzEReCTDSGM5lWecN5byoja6FELIUBdct1ISUpSm11gVwbuZ_tNowLXkLNL9Gt8e5e-9-TxCiGvpgwFo9gpuCYkVOOGesLBP66QW6c5Mf03aJkkJUVUFm6uOJmuoBGrX3_aD9QZ0fmoDqCBjvQvDQKtNHHXs3Rq97qyhRs3tqdk_N26qTe0lJXyjPw_-n-XDU9ADwj5c0XZST_C8XgKTk
CODEN	IJBHA9
CitedBy_id	crossref_primary_10_1016_j_mrl_2025_200241 crossref_primary_10_1109_JSEN_2024_3438773 crossref_primary_10_1109_RBME_2021_3121476 crossref_primary_10_1109_JBHI_2022_3220967 crossref_primary_10_1109_JBHI_2023_3266349 crossref_primary_10_1007_s13246_023_01293_w crossref_primary_10_1109_JBHI_2023_3265857 crossref_primary_10_1002_btm2_10359 crossref_primary_10_1016_j_saa_2023_123181 crossref_primary_10_1109_TCE_2023_3316514 crossref_primary_10_1109_TIM_2021_3122182 crossref_primary_10_3390_bioengineering11040306 crossref_primary_10_1002_advs_202310022 crossref_primary_10_1016_j_bspc_2022_103616 crossref_primary_10_32604_cmc_2022_020493 crossref_primary_10_1109_JBHI_2022_3167059 crossref_primary_10_1109_JBHI_2024_3499834 crossref_primary_10_3390_electronics12132923 crossref_primary_10_1016_j_measurement_2024_115446 crossref_primary_10_3390_s21217207 crossref_primary_10_1007_s10462_022_10353_8 crossref_primary_10_3390_app15137609 crossref_primary_10_1002_btm2_10502 crossref_primary_10_1088_1361_6579_ac7841 crossref_primary_10_1088_1361_6579_adae50 crossref_primary_10_1007_s11760_025_04353_8 crossref_primary_10_1021_acs_chemrev_4c00763 crossref_primary_10_1088_1361_6579_acead2 crossref_primary_10_1109_JBHI_2021_3061793 crossref_primary_10_1002_advs_202415215 crossref_primary_10_1109_TBME_2024_3434344 crossref_primary_10_1145_3731600 crossref_primary_10_1016_j_asr_2023_10_024 crossref_primary_10_1109_ACCESS_2024_3488595 crossref_primary_10_3389_fnins_2022_1047070 crossref_primary_10_1109_TIM_2023_3279448 crossref_primary_10_1038_s41551_023_01098_y crossref_primary_10_1038_s44222_024_00175_4 crossref_primary_10_3390_s23156947
Cites_doi	10.1364/BOE.7.004313 10.1145/3130905 10.1109/IEMBS.2003.1280811 10.1038/s41598-017-11507-3 10.1109/TBME.2015.2441951 10.1109/EMBC.2016.7590777 10.1007/978-1-4020-8486-7 10.1016/j.sder.2008.08.003 10.1007/s10103-017-2317-4 10.1109/JBHI.2016.2620995 10.1016/j.jash.2015.09.011 10.1161/01.CIR.36.6.805 10.1016/S0140-6736(12)61766-8 10.1109/TBME.2018.2874957
ContentType	Journal Article
Copyright	Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021
Copyright_xml	– notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021
DBID	97E RIA RIE AAYXX CITATION NPM 7QF 7QO 7QQ 7SC 7SE 7SP 7SR 7TA 7TB 7U5 8BQ 8FD F28 FR3 H8D JG9 JQ2 K9. KR7 L7M L~C L~D NAPCQ P64 7X8
DOI	10.1109/JBHI.2020.3004032
DatabaseName	IEEE Xplore (IEEE) IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Electronic Library (IEL) CrossRef PubMed Aluminium Industry Abstracts Biotechnology Research Abstracts Ceramic Abstracts Computer and Information Systems Abstracts Corrosion Abstracts Electronics & Communications Abstracts Engineered Materials Abstracts Materials Business File Mechanical & Transportation Engineering Abstracts Solid State and Superconductivity Abstracts METADEX Technology Research Database ANTE: Abstracts in New Technology & Engineering Engineering Research Database Aerospace Database Materials Research Database ProQuest Computer Science Collection ProQuest Health & Medical Complete (Alumni) Civil Engineering Abstracts Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional Nursing & Allied Health Premium Biotechnology and BioEngineering Abstracts MEDLINE - Academic
DatabaseTitle	CrossRef PubMed Materials Research Database Civil Engineering Abstracts Aluminium Industry Abstracts Technology Research Database Computer and Information Systems Abstracts – Academic Mechanical & Transportation Engineering Abstracts Electronics & Communications Abstracts ProQuest Computer Science Collection Computer and Information Systems Abstracts ProQuest Health & Medical Complete (Alumni) Ceramic Abstracts Materials Business File METADEX Biotechnology and BioEngineering Abstracts Computer and Information Systems Abstracts Professional Aerospace Database Nursing & Allied Health Premium Engineered Materials Abstracts Biotechnology Research Abstracts Solid State and Superconductivity Abstracts Engineering Research Database Corrosion Abstracts Advanced Technologies Database with Aerospace ANTE: Abstracts in New Technology & Engineering MEDLINE - Academic
DatabaseTitleList	PubMed MEDLINE - Academic Materials Research Database
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	Medicine
EISSN	2168-2208
EndPage	673
ExternalDocumentID	32750946 10_1109_JBHI_2020_3004032 9122530
Genre	orig-research Journal Article
GrantInformation_xml	– fundername: Innovation and Technology Commission funderid: 10.13039/501100003452 – fundername: Midstream Research Programme for Universities grantid: MRP/056/17X
GroupedDBID	0R~ 4.4 6IF 6IH 6IK 97E AAJGR AARMG AASAJ AAWTH ABAZT ABQJQ ABVLG ACIWK ACPRK AENEX AFRAH AGQYO AGSQL AHBIQ AKJIK AKQYR ALMA_UNASSIGNED_HOLDINGS BEFXN BFFAM BGNUA BKEBE BPEOZ EBS EJD HZ~ IFIPE IPLJI JAVBF M43 O9- OCL PQQKQ RIA RIE RNS AAYXX CITATION NPM RIG 7QF 7QO 7QQ 7SC 7SE 7SP 7SR 7TA 7TB 7U5 8BQ 8FD F28 FR3 H8D JG9 JQ2 K9. KR7 L7M L~C L~D NAPCQ P64 7X8
ID	FETCH-LOGICAL-c415t-8378ec9cc6695b3d1664bcab88895846afeb0055c5aaa4e66c2020fac2a96fe13
IEDL.DBID	RIE
ISICitedReferencesCount	46
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000626521100006&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	2168-2194 2168-2208
IngestDate	Thu Oct 02 04:52:10 EDT 2025 Sun Nov 09 05:59:13 EST 2025 Thu Apr 03 06:57:31 EDT 2025 Tue Nov 18 20:55:37 EST 2025 Sat Nov 29 04:18:16 EST 2025 Wed Aug 27 02:48:57 EDT 2025
IsPeerReviewed	true
IsScholarly	true
Issue	3
Language	English
License	https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html https://doi.org/10.15223/policy-029 https://doi.org/10.15223/policy-037
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c415t-8378ec9cc6695b3d1664bcab88895846afeb0055c5aaa4e66c2020fac2a96fe13
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23
ORCID	0000-0002-1536-8516 0000-0003-4150-5470 0000-0003-3088-1673
PMID	32750946
PQID	2498877405
PQPubID	85417
PageCount	11
ParticipantIDs	proquest_journals_2498877405 pubmed_primary_32750946 crossref_citationtrail_10_1109_JBHI_2020_3004032 ieee_primary_9122530 proquest_miscellaneous_2430662255 crossref_primary_10_1109_JBHI_2020_3004032
PublicationCentury	2000
PublicationDate	2021-03-01
PublicationDateYYYYMMDD	2021-03-01
PublicationDate_xml	– month: 03 year: 2021 text: 2021-03-01 day: 01
PublicationDecade	2020
PublicationPlace	United States
PublicationPlace_xml	– name: United States – name: Piscataway
PublicationTitle	IEEE journal of biomedical and health informatics
PublicationTitleAbbrev	JBHI
PublicationTitleAlternate	IEEE J Biomed Health Inform
PublicationYear	2021
Publisher	IEEE The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher_xml	– name: IEEE – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
References	fodor (ref12) 2010 golub (ref23) 2012; 3 ref11 ref10 ref2 ref16 härdle (ref13) 2007; 22007 ref19 sedlá?ek (ref18) 2003 sedlacek (ref17) 2005; 12 poon (ref4) 2006 association (ref24) 2014 ref25 avci (ref14) 0 ref22 ref21 alwan (ref1) 2011 (ref20) 2014 ref8 chang (ref15) 2015 ref7 ref9 ref3 ref6 ref5
References_xml	– year: 0 ident: ref14 article-title: Low-level laser (light) therapy (LLLT) in skin: Stimulating, healing, restoring publication-title: Seminars in Cutaneous Medicine and Surgery – ident: ref6 doi: 10.1364/BOE.7.004313 – ident: ref5 doi: 10.1145/3130905 – year: 2011 ident: ref1 publication-title: Global Status Report on Noncommunicable Diseases 2010 – ident: ref10 doi: 10.1109/IEMBS.2003.1280811 – ident: ref25 doi: 10.1038/s41598-017-11507-3 – ident: ref9 doi: 10.1109/TBME.2015.2441951 – ident: ref7 doi: 10.1109/EMBC.2016.7590777 – year: 2010 ident: ref12 publication-title: Aesthetic Applications of Intense Pulsed Light – ident: ref19 doi: 10.1007/978-1-4020-8486-7 – start-page: 394 year: 2015 ident: ref15 article-title: Evaluation of absorbed light dose in human skin tissue during light therapy by 630 nm LED light publication-title: Proc IEEE 12th Int Conf Networ Sens Control – ident: ref16 doi: 10.1016/j.sder.2008.08.003 – year: 2014 ident: ref20 article-title: ANSI/AAMI/ISO 81060-2: 2013 Noninvasive sphygmomanometers-Part 2: Clinical investigation of automated measurement type. 2013. Association for the Advancement of Medical Instrumentation. Arlington, VA. 2013 – ident: ref11 doi: 10.1007/s10103-017-2317-4 – ident: ref3 doi: 10.1109/JBHI.2016.2620995 – volume: 3 year: 2012 ident: ref23 publication-title: Matrix Computations – volume: 12 start-page: 427 year: 2005 ident: ref17 article-title: Digital measurement of phase difference-a comparative study of DSP algorithms publication-title: Metrol Meas Syst – year: 2014 ident: ref24 article-title: IEEE standard for wearable cuffless blood pressure measuring devices – ident: ref22 doi: 10.1016/j.jash.2015.09.011 – ident: ref21 doi: 10.1161/01.CIR.36.6.805 – ident: ref2 doi: 10.1016/S0140-6736(12)61766-8 – ident: ref8 doi: 10.1109/TBME.2018.2874957 – start-page: 639 year: 2003 ident: ref18 article-title: Digital measurement of phase difference of LF signals-a comparison of DSP algorithms publication-title: Proc IMEKO XVII World Congr (CD) – volume: 22007 year: 2007 ident: ref13 publication-title: Applied multivariate statistical analysis – start-page: 1 year: 2006 ident: ref4 article-title: M-health: The development of cuff-less and wearable blood pressure meters for use in body sensor networks publication-title: Proc IEEE/NLM Life Sci Syst Appl Workshop
SSID	ssj0000816896
Score	2.4959075
Snippet	The prevalence of hypertension has made blood pressure (BP) measurement one of the most wanted functions in wearable devices for convenient and frequent...
SourceID	proquest pubmed crossref ieee
SourceType	Aggregation Database Index Database Enrichment Source Publisher
StartPage	663
SubjectTerms	Algorithms Biomedical monitoring Blood Blood pressure cuffless blood pressure measurement EKG Electrocardiography Hypertension Lag time Medical equipment multi-wavelength photoplethysmography Older people Pressure measurement Principal component analysis Principal components analysis Reactive power Self-assessment Sensors Skin Statistical analysis Telemedicine Transit time Waveforms Wavelength Wearable technology
Title	PCA-Based Multi-Wavelength Photoplethysmography Algorithm for Cuffless Blood Pressure Measurement on Elderly Subjects
URI	https://ieeexplore.ieee.org/document/9122530 https://www.ncbi.nlm.nih.gov/pubmed/32750946 https://www.proquest.com/docview/2498877405 https://www.proquest.com/docview/2430662255
Volume	25
WOSCitedRecordID	wos000626521100006&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVIEE databaseName: IEEE Electronic Library (IEL) customDbUrl: eissn: 2168-2208 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000816896 issn: 2168-2194 databaseCode: RIE dateStart: 20130101 isFulltext: true titleUrlDefault: https://ieeexplore.ieee.org/ providerName: IEEE
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1La9wwEB7SUEov6SN9uE2CCj2VqrFXtrw67i4JaWnCHvrYm5FkORvY2GHXDuTfd0bWuj00hd4ElmWjGY3m_QG8NyqVmXWax7IccwLb5kqojOdGGNQfnFG-bu3H1_ziYrxYqPkOfBxqYZxzPvnMfaKhj-WXje3IVXasEuQ-gQb6gzyXfa3W4E_xABIejmuEA44HMQ1BzCRWx1-mZ5_RGByhjUpsKwjERlBrc0Wa7x83kodYuV_b9LfO6ZP_-9-nsBe0Szbp2eEZ7Lj6OTw6D_Hzfejmswmf4sVVMl95y39qAp6oL9slmy-blrLJiXLXoZE1m6wum_VVu7xmqNyyWVdVKxSNbErp7qwvLVw7dv7b0ciamp0Q8vfqjqFQIi_P5gV8Pz35NjvjAXiBW7zPW05N5p1V1kqpMiPKRMrUWG3QWlaksOiKEIeyzGZa69RJaWlrK21HWsnKJeIl7NZN7V4DM5UUpU7QaNRx6lCkSYcqTmyU1igJyjKCeLv5hQ1dyQkcY1V46yRWBZGuoPWLQLoIPgyv3PQtOf41eZ_oMkwMJIngYEvhIhzaTYGWKIrcHFXYCN4Nj_G4UQxF167paI6gnvloiEXwqueMYe0tQ735-zffwuMRJcT4BLYD2G3XnTuEh_a2vdqsj5CnF-Mjz9O_AKoo77c
linkProvider	IEEE
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3Nb9MwFH-aBgIuDBgfgQFG4oTwlsSJOx_balMHbdXDgN0i23HWSV2C2gSJ_573nDTjsCFxsxTHifyen9_3D-CjUYlMrdM8lPkxJ7BtroRK-cAIg_qDM8rXrX2fDubz44sLtdiBz30tjHPOJ5-5Qxr6WH5e2YZcZUcqQu4TaKDfS5MkDttqrd6j4iEkPCBXjAOORzHpwphRqI6-jCZnaA7GaKUS4wqCsRHU3FyR7vvXneRBVu7WN_29c7r3f3_8BB53-iUbtgzxFHZc-QwezLoI-j40i_GQj_DqypmvveU_NEFPlJf1ki2WVU355ES7666VNRuuLqv1Vb28ZqjesnFTFCsUjmxECe-sLS5cOza7cTWyqmQnhP29-s1QLJGfZ_Mcvp2enI8nvINe4BZv9JpTm3lnlbVSqtSIPJIyMVYbtJcVqSy6IMyhNLWp1jpxUlra2kLbWCtZuEi8gN2yKt0rYKaQItcRmo06TBwKNelQyQmN0hplQZ4HEG43P7NdX3KCx1hl3j4JVUaky2j9rCNdAJ_6V362TTn-NXmf6NJP7EgSwMGWwll3bDcZ2qIodAeoxAbwoX-MB46iKLp0VUNzBHXNR1MsgJctZ_Rrbxnq9e3ffA8PJ-ezaTY9m399A49iSo_x6WwHsFuvG_cW7ttf9dVm_c5z9h-f4PIW
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%3Ajournal&rft.genre=article&rft.atitle=PCA-Based+Multi-Wavelength+Photoplethysmography+Algorithm+for+Cuffless+Blood+Pressure+Measurement+on+Elderly+Subjects&rft.jtitle=IEEE+journal+of+biomedical+and+health+informatics&rft.au=Liu%2C+Jing&rft.au=Qiu%2C+Shirong&rft.au=Luo%2C+Ningqi&rft.au=Lau%2C+Sze-Kei&rft.date=2021-03-01&rft.issn=2168-2194&rft.eissn=2168-2208&rft.volume=25&rft.issue=3&rft.spage=663&rft.epage=673&rft_id=info:doi/10.1109%2FJBHI.2020.3004032&rft.externalDBID=n%2Fa&rft.externalDocID=10_1109_JBHI_2020_3004032
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2168-2194&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2168-2194&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2168-2194&client=summon