Intrinsic Mode Analysis of Human Heartbeat Time Series View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2010-04

AUTHORS

Jia-Rong Yeh, Wei-Zen Sun, Jiann-Shing Shieh, Norden E. Huang

ABSTRACT

The human heartbeat interval is determined by complex nerve control and environmental inputs. As a result, the heartbeat interval for a human is a complex time series, as shown by previous studies. Most of the analysis algorithms proposed for characterizing the profile of heartbeat time series, such as detrended fluctuation analysis and multi-scale entropy, are based on various characteristics of dynamics. In this study, we present an empirical mode decomposition-based intrinsic mode analysis, which uses the appearance energy index (AEI) to quantify the property of long-term correlation, and structure index (SI) to characterize the internal modulation of data. This presented algorithm was used to investigate the human heartbeat time series downloaded from PhysioBank. We found the profiles of human heartbeat time series of subjects with congestive heart failure (CHF) or atrial fibrillation (AF) are significantly different from those of healthy subjects in internal modulation as shown by SI. Moreover, AEI is the critical characteristics for verifying subjects with CHF from subjects with AF in a degree of long-term correlation. Both AEI and SI contribute to presenting the characteristic profiles of a human heartbeat time series. More... »

PAGES

1337-1344

References to SciGraph publications

  • 2001-07. Application of empirical mode decomposition to heart rate variability analysis in MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s10439-010-9939-z

    DOI

    http://dx.doi.org/10.1007/s10439-010-9939-z

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1050965037

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/20119846


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1102", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Cardiorespiratory Medicine and Haematology", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Medical and Health Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Algorithms", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Atrial Fibrillation", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Computer Simulation", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Diagnosis, Computer-Assisted", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Electrocardiography", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Heart Failure", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Heart Rate", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Humans", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Models, Cardiovascular", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Signal Processing, Computer-Assisted", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Yuan Ze University", 
              "id": "https://www.grid.ac/institutes/grid.413050.3", 
              "name": [
                "Department of Mechanical Engineering, Yuan Ze University, 135 Yuan-Tung Rd., 320, Chung-Li, Taoyuan, Taiwan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Yeh", 
            "givenName": "Jia-Rong", 
            "id": "sg:person.0734027261.66", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0734027261.66"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "National Taiwan University", 
              "id": "https://www.grid.ac/institutes/grid.19188.39", 
              "name": [
                "Department of Anaesthesiology, College of Medicine, National Taiwan University, Taipei, Taiwan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Sun", 
            "givenName": "Wei-Zen", 
            "id": "sg:person.01010602037.06", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01010602037.06"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Yuan Ze University", 
              "id": "https://www.grid.ac/institutes/grid.413050.3", 
              "name": [
                "Department of Mechanical Engineering, Yuan Ze University, 135 Yuan-Tung Rd., 320, Chung-Li, Taoyuan, Taiwan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Shieh", 
            "givenName": "Jiann-Shing", 
            "id": "sg:person.01155051311.51", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01155051311.51"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "National Central University", 
              "id": "https://www.grid.ac/institutes/grid.37589.30", 
              "name": [
                "Research Center for Adaptive Data Analysis, National Central University, Taoyuan, Taiwan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Huang", 
            "givenName": "Norden E.", 
            "id": "sg:person.01053733255.82", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01053733255.82"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1093/oxfordjournals.eurheartj.a014868", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008382500"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0197-4580(01)00266-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010300730"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1037/0033-2909.114.2.296", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016094562"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/j.1749-6632.2001.tb02755.x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021587223"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jbi.2005.02.008", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037399825"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1098/rspa.2003.1221", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045430544"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf02345370", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046047496", 
              "https://doi.org/10.1007/bf02345370"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf02345370", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046047496", 
              "https://doi.org/10.1007/bf02345370"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1098/rspa.1998.0193", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048418364"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1063/1.166141", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1057739643"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevlett.70.1343", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060806405"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevlett.70.1343", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060806405"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevlett.89.068102", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060825158"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevlett.89.068102", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060825158"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevlett.90.108103", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060826440"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevlett.90.108103", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060826440"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/10.959324", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061086001"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/lsp.2003.821662", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061376228"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1137/1010093", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1062860082"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1142/s0219691304000561", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1063003803"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2307/1390903", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1069468336"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1152/ajpheart.2000.278.6.h2039", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1074650018"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1152/ajpheart.1995.268.4.h1441", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1082485024"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1142/9789812703347_0003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1088721885"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2010-04", 
        "datePublishedReg": "2010-04-01", 
        "description": "The human heartbeat interval is determined by complex nerve control and environmental inputs. As a result, the heartbeat interval for a human is a complex time series, as shown by previous studies. Most of the analysis algorithms proposed for characterizing the profile of heartbeat time series, such as detrended fluctuation analysis and multi-scale entropy, are based on various characteristics of dynamics. In this study, we present an empirical mode decomposition-based intrinsic mode analysis, which uses the appearance energy index (AEI) to quantify the property of long-term correlation, and structure index (SI) to characterize the internal modulation of data. This presented algorithm was used to investigate the human heartbeat time series downloaded from PhysioBank. We found the profiles of human heartbeat time series of subjects with congestive heart failure (CHF) or atrial fibrillation (AF) are significantly different from those of healthy subjects in internal modulation as shown by SI. Moreover, AEI is the critical characteristics for verifying subjects with CHF from subjects with AF in a degree of long-term correlation. Both AEI and SI contribute to presenting the characteristic profiles of a human heartbeat time series.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/s10439-010-9939-z", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1087247", 
            "issn": [
              "0145-3068", 
              "1573-9686"
            ], 
            "name": "Annals of Biomedical Engineering", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "4", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "38"
          }
        ], 
        "name": "Intrinsic Mode Analysis of Human Heartbeat Time Series", 
        "pagination": "1337-1344", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "f2c7a36720a199e178f0088b9190ac0e86f23869919a9b80724949a0fd0ffde9"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "20119846"
            ]
          }, 
          {
            "name": "nlm_unique_id", 
            "type": "PropertyValue", 
            "value": [
              "0361512"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s10439-010-9939-z"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1050965037"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s10439-010-9939-z", 
          "https://app.dimensions.ai/details/publication/pub.1050965037"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T09:50", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000347_0000000347/records_89786_00000002.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "http://link.springer.com/10.1007%2Fs10439-010-9939-z"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s10439-010-9939-z'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s10439-010-9939-z'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10439-010-9939-z'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10439-010-9939-z'


     

    This table displays all metadata directly associated to this object as RDF triples.

    197 TRIPLES      21 PREDICATES      59 URIs      31 LITERALS      19 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s10439-010-9939-z schema:about N520ee689f23d403cb261776f8d2b0121
    2 N7f95d80736fd461e922fa89a87751dd9
    3 N84481a00808e4d31ab2bd39913070ed5
    4 N8eba53ad2ea84665aca9ae38d6497fc7
    5 N95ae2fcb5ba54c5d8ca52a806bff5275
    6 Nade44dcafec244ed8761874ef15f462b
    7 Nd84bc1add0874116a0f74f4dfacb8deb
    8 Ne676c216786544dd80aeb76b2bd39a84
    9 Nfac5cb8afdd94e9183e53ac97d2e101f
    10 Nff729cc505484708980ff9c1b1e8cbff
    11 anzsrc-for:11
    12 anzsrc-for:1102
    13 schema:author N1821bb25b53a4a3ca56580016fd3edac
    14 schema:citation sg:pub.10.1007/bf02345370
    15 https://doi.org/10.1016/j.jbi.2005.02.008
    16 https://doi.org/10.1016/s0197-4580(01)00266-4
    17 https://doi.org/10.1037/0033-2909.114.2.296
    18 https://doi.org/10.1063/1.166141
    19 https://doi.org/10.1093/oxfordjournals.eurheartj.a014868
    20 https://doi.org/10.1098/rspa.1998.0193
    21 https://doi.org/10.1098/rspa.2003.1221
    22 https://doi.org/10.1103/physrevlett.70.1343
    23 https://doi.org/10.1103/physrevlett.89.068102
    24 https://doi.org/10.1103/physrevlett.90.108103
    25 https://doi.org/10.1109/10.959324
    26 https://doi.org/10.1109/lsp.2003.821662
    27 https://doi.org/10.1111/j.1749-6632.2001.tb02755.x
    28 https://doi.org/10.1137/1010093
    29 https://doi.org/10.1142/9789812703347_0003
    30 https://doi.org/10.1142/s0219691304000561
    31 https://doi.org/10.1152/ajpheart.1995.268.4.h1441
    32 https://doi.org/10.1152/ajpheart.2000.278.6.h2039
    33 https://doi.org/10.2307/1390903
    34 schema:datePublished 2010-04
    35 schema:datePublishedReg 2010-04-01
    36 schema:description The human heartbeat interval is determined by complex nerve control and environmental inputs. As a result, the heartbeat interval for a human is a complex time series, as shown by previous studies. Most of the analysis algorithms proposed for characterizing the profile of heartbeat time series, such as detrended fluctuation analysis and multi-scale entropy, are based on various characteristics of dynamics. In this study, we present an empirical mode decomposition-based intrinsic mode analysis, which uses the appearance energy index (AEI) to quantify the property of long-term correlation, and structure index (SI) to characterize the internal modulation of data. This presented algorithm was used to investigate the human heartbeat time series downloaded from PhysioBank. We found the profiles of human heartbeat time series of subjects with congestive heart failure (CHF) or atrial fibrillation (AF) are significantly different from those of healthy subjects in internal modulation as shown by SI. Moreover, AEI is the critical characteristics for verifying subjects with CHF from subjects with AF in a degree of long-term correlation. Both AEI and SI contribute to presenting the characteristic profiles of a human heartbeat time series.
    37 schema:genre research_article
    38 schema:inLanguage en
    39 schema:isAccessibleForFree false
    40 schema:isPartOf Nde59fa2c62f04d44b9db02b0927f406a
    41 Nf6eff746bcfb454db02495da393fce9e
    42 sg:journal.1087247
    43 schema:name Intrinsic Mode Analysis of Human Heartbeat Time Series
    44 schema:pagination 1337-1344
    45 schema:productId N2ee4f59b39b74b44a1a2e5a869889f8f
    46 N679ac9bd91ed4cef9bdf1f486c2f0c00
    47 N94a026371c9840c4b1a227797d13242f
    48 Ne79fdef9b2e14d8dab8df5ca4a09f1eb
    49 Ned02e778b7d14daf9af0e1c500960c46
    50 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050965037
    51 https://doi.org/10.1007/s10439-010-9939-z
    52 schema:sdDatePublished 2019-04-11T09:50
    53 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    54 schema:sdPublisher N1d72269cb0224659b0c6700b87d20f45
    55 schema:url http://link.springer.com/10.1007%2Fs10439-010-9939-z
    56 sgo:license sg:explorer/license/
    57 sgo:sdDataset articles
    58 rdf:type schema:ScholarlyArticle
    59 N1821bb25b53a4a3ca56580016fd3edac rdf:first sg:person.0734027261.66
    60 rdf:rest N437b248fce394133bfd2dc3bc8ab46f1
    61 N1d72269cb0224659b0c6700b87d20f45 schema:name Springer Nature - SN SciGraph project
    62 rdf:type schema:Organization
    63 N2ee4f59b39b74b44a1a2e5a869889f8f schema:name pubmed_id
    64 schema:value 20119846
    65 rdf:type schema:PropertyValue
    66 N437b248fce394133bfd2dc3bc8ab46f1 rdf:first sg:person.01010602037.06
    67 rdf:rest Nc0cf084cd5344c88b4632f4dd30b643a
    68 N520ee689f23d403cb261776f8d2b0121 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    69 schema:name Heart Rate
    70 rdf:type schema:DefinedTerm
    71 N679ac9bd91ed4cef9bdf1f486c2f0c00 schema:name doi
    72 schema:value 10.1007/s10439-010-9939-z
    73 rdf:type schema:PropertyValue
    74 N7f95d80736fd461e922fa89a87751dd9 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    75 schema:name Heart Failure
    76 rdf:type schema:DefinedTerm
    77 N84481a00808e4d31ab2bd39913070ed5 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    78 schema:name Humans
    79 rdf:type schema:DefinedTerm
    80 N8eba53ad2ea84665aca9ae38d6497fc7 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    81 schema:name Atrial Fibrillation
    82 rdf:type schema:DefinedTerm
    83 N92626adf608f49d8a1d06fa4788de063 rdf:first sg:person.01053733255.82
    84 rdf:rest rdf:nil
    85 N94a026371c9840c4b1a227797d13242f schema:name dimensions_id
    86 schema:value pub.1050965037
    87 rdf:type schema:PropertyValue
    88 N95ae2fcb5ba54c5d8ca52a806bff5275 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    89 schema:name Models, Cardiovascular
    90 rdf:type schema:DefinedTerm
    91 Nade44dcafec244ed8761874ef15f462b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    92 schema:name Algorithms
    93 rdf:type schema:DefinedTerm
    94 Nc0cf084cd5344c88b4632f4dd30b643a rdf:first sg:person.01155051311.51
    95 rdf:rest N92626adf608f49d8a1d06fa4788de063
    96 Nd84bc1add0874116a0f74f4dfacb8deb schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    97 schema:name Signal Processing, Computer-Assisted
    98 rdf:type schema:DefinedTerm
    99 Nde59fa2c62f04d44b9db02b0927f406a schema:volumeNumber 38
    100 rdf:type schema:PublicationVolume
    101 Ne676c216786544dd80aeb76b2bd39a84 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    102 schema:name Diagnosis, Computer-Assisted
    103 rdf:type schema:DefinedTerm
    104 Ne79fdef9b2e14d8dab8df5ca4a09f1eb schema:name nlm_unique_id
    105 schema:value 0361512
    106 rdf:type schema:PropertyValue
    107 Ned02e778b7d14daf9af0e1c500960c46 schema:name readcube_id
    108 schema:value f2c7a36720a199e178f0088b9190ac0e86f23869919a9b80724949a0fd0ffde9
    109 rdf:type schema:PropertyValue
    110 Nf6eff746bcfb454db02495da393fce9e schema:issueNumber 4
    111 rdf:type schema:PublicationIssue
    112 Nfac5cb8afdd94e9183e53ac97d2e101f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    113 schema:name Computer Simulation
    114 rdf:type schema:DefinedTerm
    115 Nff729cc505484708980ff9c1b1e8cbff schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    116 schema:name Electrocardiography
    117 rdf:type schema:DefinedTerm
    118 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
    119 schema:name Medical and Health Sciences
    120 rdf:type schema:DefinedTerm
    121 anzsrc-for:1102 schema:inDefinedTermSet anzsrc-for:
    122 schema:name Cardiorespiratory Medicine and Haematology
    123 rdf:type schema:DefinedTerm
    124 sg:journal.1087247 schema:issn 0145-3068
    125 1573-9686
    126 schema:name Annals of Biomedical Engineering
    127 rdf:type schema:Periodical
    128 sg:person.01010602037.06 schema:affiliation https://www.grid.ac/institutes/grid.19188.39
    129 schema:familyName Sun
    130 schema:givenName Wei-Zen
    131 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01010602037.06
    132 rdf:type schema:Person
    133 sg:person.01053733255.82 schema:affiliation https://www.grid.ac/institutes/grid.37589.30
    134 schema:familyName Huang
    135 schema:givenName Norden E.
    136 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01053733255.82
    137 rdf:type schema:Person
    138 sg:person.01155051311.51 schema:affiliation https://www.grid.ac/institutes/grid.413050.3
    139 schema:familyName Shieh
    140 schema:givenName Jiann-Shing
    141 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01155051311.51
    142 rdf:type schema:Person
    143 sg:person.0734027261.66 schema:affiliation https://www.grid.ac/institutes/grid.413050.3
    144 schema:familyName Yeh
    145 schema:givenName Jia-Rong
    146 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0734027261.66
    147 rdf:type schema:Person
    148 sg:pub.10.1007/bf02345370 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046047496
    149 https://doi.org/10.1007/bf02345370
    150 rdf:type schema:CreativeWork
    151 https://doi.org/10.1016/j.jbi.2005.02.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037399825
    152 rdf:type schema:CreativeWork
    153 https://doi.org/10.1016/s0197-4580(01)00266-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010300730
    154 rdf:type schema:CreativeWork
    155 https://doi.org/10.1037/0033-2909.114.2.296 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016094562
    156 rdf:type schema:CreativeWork
    157 https://doi.org/10.1063/1.166141 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057739643
    158 rdf:type schema:CreativeWork
    159 https://doi.org/10.1093/oxfordjournals.eurheartj.a014868 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008382500
    160 rdf:type schema:CreativeWork
    161 https://doi.org/10.1098/rspa.1998.0193 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048418364
    162 rdf:type schema:CreativeWork
    163 https://doi.org/10.1098/rspa.2003.1221 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045430544
    164 rdf:type schema:CreativeWork
    165 https://doi.org/10.1103/physrevlett.70.1343 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060806405
    166 rdf:type schema:CreativeWork
    167 https://doi.org/10.1103/physrevlett.89.068102 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060825158
    168 rdf:type schema:CreativeWork
    169 https://doi.org/10.1103/physrevlett.90.108103 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060826440
    170 rdf:type schema:CreativeWork
    171 https://doi.org/10.1109/10.959324 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061086001
    172 rdf:type schema:CreativeWork
    173 https://doi.org/10.1109/lsp.2003.821662 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061376228
    174 rdf:type schema:CreativeWork
    175 https://doi.org/10.1111/j.1749-6632.2001.tb02755.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1021587223
    176 rdf:type schema:CreativeWork
    177 https://doi.org/10.1137/1010093 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062860082
    178 rdf:type schema:CreativeWork
    179 https://doi.org/10.1142/9789812703347_0003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1088721885
    180 rdf:type schema:CreativeWork
    181 https://doi.org/10.1142/s0219691304000561 schema:sameAs https://app.dimensions.ai/details/publication/pub.1063003803
    182 rdf:type schema:CreativeWork
    183 https://doi.org/10.1152/ajpheart.1995.268.4.h1441 schema:sameAs https://app.dimensions.ai/details/publication/pub.1082485024
    184 rdf:type schema:CreativeWork
    185 https://doi.org/10.1152/ajpheart.2000.278.6.h2039 schema:sameAs https://app.dimensions.ai/details/publication/pub.1074650018
    186 rdf:type schema:CreativeWork
    187 https://doi.org/10.2307/1390903 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069468336
    188 rdf:type schema:CreativeWork
    189 https://www.grid.ac/institutes/grid.19188.39 schema:alternateName National Taiwan University
    190 schema:name Department of Anaesthesiology, College of Medicine, National Taiwan University, Taipei, Taiwan
    191 rdf:type schema:Organization
    192 https://www.grid.ac/institutes/grid.37589.30 schema:alternateName National Central University
    193 schema:name Research Center for Adaptive Data Analysis, National Central University, Taoyuan, Taiwan
    194 rdf:type schema:Organization
    195 https://www.grid.ac/institutes/grid.413050.3 schema:alternateName Yuan Ze University
    196 schema:name Department of Mechanical Engineering, Yuan Ze University, 135 Yuan-Tung Rd., 320, Chung-Li, Taoyuan, Taiwan
    197 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...