<?xml version="1.0" encoding="utf-8"?>
<TEI xmlns="http://www.tei-c.org/ns/1.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:hal="http://hal.archives-ouvertes.fr/" xmlns:gml="http://www.opengis.net/gml/3.3/" xmlns:gmlce="http://www.opengis.net/gml/3.3/ce" version="1.1" xsi:schemaLocation="http://www.tei-c.org/ns/1.0 http://api.archives-ouvertes.fr/documents/aofr-sword.xsd">
  <teiHeader>
    <fileDesc>
      <titleStmt>
        <title>HAL TEI export of hal-05265485</title>
      </titleStmt>
      <publicationStmt>
        <distributor>CCSD</distributor>
        <availability status="restricted">
          <licence target="https://creativecommons.org/publicdomain/zero/1.0/">CC0 1.0 - Universal</licence>
        </availability>
        <date when="2026-05-20T18:39:42+02:00"/>
      </publicationStmt>
      <sourceDesc>
        <p part="N">HAL API Platform</p>
      </sourceDesc>
    </fileDesc>
  </teiHeader>
  <text>
    <body>
      <listBibl>
        <biblFull>
          <titleStmt>
            <title xml:lang="en">A physiology-driven deep learning-based pipeline for ECG segmentation</title>
            <author role="aut">
              <persName>
                <forename type="first">Alaa</forename>
                <surname>Salama</surname>
              </persName>
              <idno type="idhal" notation="numeric">1583701</idno>
              <idno type="halauthorid" notation="string">3781063-1583701</idno>
              <idno type="ORCID">https://orcid.org/0009-0005-1944-7800</idno>
              <affiliation ref="#struct-182223"/>
            </author>
            <author role="aut">
              <persName>
                <forename type="first">Amar</forename>
                <surname>Kachenoura</surname>
              </persName>
              <idno type="halauthorid">193618-0</idno>
              <affiliation ref="#struct-182223"/>
            </author>
            <author role="aut">
              <persName>
                <forename type="first">Salman Almuhammad</forename>
                <surname>Alali</surname>
              </persName>
              <email type="md5">5eabd065ec067445eaf6b34998c788e9</email>
              <email type="domain">univ-rennes.fr</email>
              <idno type="idhal" notation="string">salman-almuhammad-alali</idno>
              <idno type="idhal" notation="numeric">1445318</idno>
              <idno type="halauthorid" notation="string">3627138-1445318</idno>
              <idno type="ORCID">https://orcid.org/0009-0003-9448-9221</idno>
              <affiliation ref="#struct-182223"/>
            </author>
            <author role="aut">
              <persName>
                <forename type="first">Guy</forename>
                <surname>Carrault</surname>
              </persName>
              <idno type="halauthorid">129605-0</idno>
              <affiliation ref="#struct-182223"/>
            </author>
            <author role="aut">
              <persName>
                <forename type="first">Lotfi</forename>
                <surname>Senhadji</surname>
              </persName>
              <email type="md5">90472cc13e45cb24ef8051a4aef6f2f4</email>
              <email type="domain">univ-rennes1.fr</email>
              <idno type="idhal" notation="string">lotfi-senhadji</idno>
              <idno type="idhal" notation="numeric">404</idno>
              <idno type="halauthorid" notation="string">3885-404</idno>
              <idno type="RESEARCHERID">http://www.researcherid.com/rid/E-5903-2013</idno>
              <idno type="ORCID">https://orcid.org/0000-0001-9434-6341</idno>
              <idno type="IDREF">https://www.idref.fr/110173740</idno>
              <idno type="RESEARCHERID">http://www.researcherid.com/rid/http://www.researcherid.com/rid/E-5903-2013</idno>
              <affiliation ref="#struct-182223"/>
            </author>
            <author role="crp">
              <persName>
                <forename type="first">Ahmad</forename>
                <surname>Karfoul</surname>
              </persName>
              <email type="md5">f24be49cc58fae67db153fed104462ba</email>
              <email type="domain">univ-rennes1.fr</email>
              <idno type="idhal" notation="string">ahmad-karfoul</idno>
              <idno type="idhal" notation="numeric">737855</idno>
              <idno type="halauthorid" notation="string">9723-737855</idno>
              <idno type="ORCID">https://orcid.org/0000-0002-3977-9141</idno>
              <idno type="IDREF">https://www.idref.fr/150393458</idno>
              <affiliation ref="#struct-182223"/>
            </author>
            <editor role="depositor">
              <persName>
                <forename>Laurent</forename>
                <surname>Jonchère</surname>
              </persName>
              <email type="md5">dc1f1e9bdb3dc2065f8bf1bfd5663118</email>
              <email type="domain">univ-rennes.fr</email>
            </editor>
            <funder ref="#projanr-98242"/>
            <funder>PrepRisC and DeMUG projects of the ARED program of Région Bretagne</funder>
          </titleStmt>
          <editionStmt>
            <edition n="v1" type="current">
              <date type="whenSubmitted">2026-02-19 10:58:42</date>
              <date type="whenModified">2026-05-05 15:53:44</date>
              <date type="whenReleased">2026-02-19 10:58:44</date>
              <date type="whenProduced">2026-02</date>
              <date type="whenEndEmbargoed">2026-03-17</date>
              <ref type="file" target="https://univ-rennes.hal.science/hal-05265485v1/document">
                <date notBefore="2026-03-17"/>
              </ref>
              <ref type="file" subtype="author" n="1" target="https://univ-rennes.hal.science/hal-05265485v1/file/Salama%20-%202025%20-%20A%20physiology-driven%20deep%20learning-based%20pipeline%20for%20ECG%20segmentation%20_8__2_BSPC_2025_Alaa_.pdf" id="file-5518589-4723484">
                <date notBefore="2026-03-17"/>
              </ref>
              <ref type="annex" n="0" target="https://univ-rennes.hal.science/hal-05265485v1/file/1-s2.0-S174680942501119X-mmc1.pdf" id="file-5518589-4723485">
                <date notBefore="2026-02-19"/>
              </ref>
            </edition>
            <respStmt>
              <resp>contributor</resp>
              <name key="113861">
                <persName>
                  <forename>Laurent</forename>
                  <surname>Jonchère</surname>
                </persName>
                <email type="md5">dc1f1e9bdb3dc2065f8bf1bfd5663118</email>
                <email type="domain">univ-rennes.fr</email>
              </name>
            </respStmt>
          </editionStmt>
          <publicationStmt>
            <distributor>CCSD</distributor>
            <idno type="halId">hal-05265485</idno>
            <idno type="halUri">https://univ-rennes.hal.science/hal-05265485</idno>
            <idno type="halBibtex">salama:hal-05265485</idno>
            <idno type="halRefHtml">&lt;i&gt;Biomedical Signal Processing and Control&lt;/i&gt;, 2026, 112, pp.108608. &lt;a target="_blank" href="https://dx.doi.org/10.1016/j.bspc.2025.108608"&gt;&amp;#x27E8;10.1016/j.bspc.2025.108608&amp;#x27E9;&lt;/a&gt;</idno>
            <idno type="halRef">Biomedical Signal Processing and Control, 2026, 112, pp.108608. &amp;#x27E8;10.1016/j.bspc.2025.108608&amp;#x27E9;</idno>
            <availability status="restricted">
              <licence target="https://creativecommons.org/licenses/by-nc/4.0/">CC BY-NC 4.0 - Attribution - Non-commercial use<ref corresp="#file-5518589-4723484"/><ref corresp="#file-5518589-4723485"/></licence>
            </availability>
          </publicationStmt>
          <seriesStmt>
            <idno type="stamp" n="UNIV-RENNES1">Université de Rennes 1</idno>
            <idno type="stamp" n="LTSI" corresp="INSERM">Laboratoire Traitement du Signal et de l'Image</idno>
            <idno type="stamp" n="STATS-UR1">Statistiques-HAL-UR1</idno>
            <idno type="stamp" n="UR1-HAL">Publications labos UR1 dans HAL-Rennes 1</idno>
            <idno type="stamp" n="UR1-MATH-STIC">UR1 - publications Maths-STIC</idno>
            <idno type="stamp" n="TEST-UR-CSS">TEST Université de Rennes CSS</idno>
            <idno type="stamp" n="UNIV-RENNES">Université de Rennes</idno>
            <idno type="stamp" n="ANR">ANR</idno>
            <idno type="stamp" n="UR1-MATH-NUM">Pôle UnivRennes - Mathématiques - Numérique </idno>
            <idno type="stamp" n="UR1-BIO-SA">Pôle UnivRennes - Biologie-Santé</idno>
            <idno type="stamp" n="PEPR_SANTENUM">PEPR Santé numérique</idno>
          </seriesStmt>
          <notesStmt>
            <note type="audience" n="2">International</note>
            <note type="popular" n="0">No</note>
            <note type="peer" n="1">Yes</note>
          </notesStmt>
          <sourceDesc>
            <biblStruct>
              <analytic>
                <title xml:lang="en">A physiology-driven deep learning-based pipeline for ECG segmentation</title>
                <author role="aut">
                  <persName>
                    <forename type="first">Alaa</forename>
                    <surname>Salama</surname>
                  </persName>
                  <idno type="idhal" notation="numeric">1583701</idno>
                  <idno type="halauthorid" notation="string">3781063-1583701</idno>
                  <idno type="ORCID">https://orcid.org/0009-0005-1944-7800</idno>
                  <affiliation ref="#struct-182223"/>
                </author>
                <author role="aut">
                  <persName>
                    <forename type="first">Amar</forename>
                    <surname>Kachenoura</surname>
                  </persName>
                  <idno type="halauthorid">193618-0</idno>
                  <affiliation ref="#struct-182223"/>
                </author>
                <author role="aut">
                  <persName>
                    <forename type="first">Salman Almuhammad</forename>
                    <surname>Alali</surname>
                  </persName>
                  <email type="md5">5eabd065ec067445eaf6b34998c788e9</email>
                  <email type="domain">univ-rennes.fr</email>
                  <idno type="idhal" notation="string">salman-almuhammad-alali</idno>
                  <idno type="idhal" notation="numeric">1445318</idno>
                  <idno type="halauthorid" notation="string">3627138-1445318</idno>
                  <idno type="ORCID">https://orcid.org/0009-0003-9448-9221</idno>
                  <affiliation ref="#struct-182223"/>
                </author>
                <author role="aut">
                  <persName>
                    <forename type="first">Guy</forename>
                    <surname>Carrault</surname>
                  </persName>
                  <idno type="halauthorid">129605-0</idno>
                  <affiliation ref="#struct-182223"/>
                </author>
                <author role="aut">
                  <persName>
                    <forename type="first">Lotfi</forename>
                    <surname>Senhadji</surname>
                  </persName>
                  <email type="md5">90472cc13e45cb24ef8051a4aef6f2f4</email>
                  <email type="domain">univ-rennes1.fr</email>
                  <idno type="idhal" notation="string">lotfi-senhadji</idno>
                  <idno type="idhal" notation="numeric">404</idno>
                  <idno type="halauthorid" notation="string">3885-404</idno>
                  <idno type="RESEARCHERID">http://www.researcherid.com/rid/E-5903-2013</idno>
                  <idno type="ORCID">https://orcid.org/0000-0001-9434-6341</idno>
                  <idno type="IDREF">https://www.idref.fr/110173740</idno>
                  <idno type="RESEARCHERID">http://www.researcherid.com/rid/http://www.researcherid.com/rid/E-5903-2013</idno>
                  <affiliation ref="#struct-182223"/>
                </author>
                <author role="crp">
                  <persName>
                    <forename type="first">Ahmad</forename>
                    <surname>Karfoul</surname>
                  </persName>
                  <email type="md5">f24be49cc58fae67db153fed104462ba</email>
                  <email type="domain">univ-rennes1.fr</email>
                  <idno type="idhal" notation="string">ahmad-karfoul</idno>
                  <idno type="idhal" notation="numeric">737855</idno>
                  <idno type="halauthorid" notation="string">9723-737855</idno>
                  <idno type="ORCID">https://orcid.org/0000-0002-3977-9141</idno>
                  <idno type="IDREF">https://www.idref.fr/150393458</idno>
                  <affiliation ref="#struct-182223"/>
                </author>
              </analytic>
              <monogr>
                <idno type="halJournalId" status="VALID">11194</idno>
                <idno type="issn">1746-8094</idno>
                <title level="j">Biomedical Signal Processing and Control</title>
                <imprint>
                  <publisher>Elsevier</publisher>
                  <biblScope unit="volume">112</biblScope>
                  <biblScope unit="pp">108608</biblScope>
                  <date type="datePub">2026-02</date>
                </imprint>
              </monogr>
              <idno type="doi">10.1016/j.bspc.2025.108608</idno>
              <relatedItem target="https://doi.org/10.13026/C24K53" type="Cites" subtype="http://purl.org/coar/resource_type/c_ddb1"/>
            </biblStruct>
          </sourceDesc>
          <profileDesc>
            <langUsage>
              <language ident="en">English</language>
            </langUsage>
            <textClass>
              <keywords scheme="author">
                <term xml:lang="en">Electrocardiography</term>
                <term xml:lang="en">ECG segmentation</term>
                <term xml:lang="en">Multi-head attention</term>
                <term xml:lang="en">BiLSTM</term>
              </keywords>
              <classCode scheme="halDomain" n="spi.signal">Engineering Sciences [physics]/Signal and Image processing</classCode>
              <classCode scheme="halDomain" n="info.info-ai">Computer Science [cs]/Artificial Intelligence [cs.AI]</classCode>
              <classCode scheme="halDomain" n="sdv.ib">Life Sciences [q-bio]/Bioengineering</classCode>
              <classCode scheme="halTypology" n="ART">Journal articles</classCode>
              <classCode scheme="halOldTypology" n="ART">Journal articles</classCode>
              <classCode scheme="halTreeTypology" n="ART">Journal articles</classCode>
            </textClass>
            <abstract xml:lang="en">
              <p>Knowing the durations and amplitudes of cardiac waves (P, QRS, and T) constituting the ElectroCardioGram (ECG) signal is crucial for diagnosing cardiac pathologies or predicting adverse events. Segmenting ECG waves visually by an expert can be laborious, highly time-consuming, and subjective. To cope with these limitations, an automatic segmentation of these waves emerges as the most sensible solution. However, accurate automatic segmentation of ECG waves is challenging due to the contamination of ECG signals by various types of noise and artefacts that can obscure or distort the waveforms. In this paper, a new supervised automatic ECG wave segmentation pipeline is proposed. It mainly relies on three stages. A shallow preprocessing stage that supports quasi-real-time data analysis. The second stage consists of a new multi-head attention-based CNN-LSTM model for ECG segmentation. The last stage includes a physiology-driven postprocessing algorithm aimed at addressing false positives in ECG segmentation, which significantly affects the evaluation of ECG segmentation methods. The effectiveness of the proposed three-stage pipeline compared to two standard unsupervised ECG segmentation pipelines and a recent deep learning-based approach is evaluated in this paper, using the well-known PhysioNet’s QT database. The obtained results demonstrate that the proposed pipeline outperforms the existing ones, particularly in the challenging segmentation of P and  waves. The good behaviors of the proposed model also confirm the usefulness of both the use of a multi-head attention layer and the additional postprocessing algorithm.</p>
            </abstract>
          </profileDesc>
        </biblFull>
      </listBibl>
    </body>
    <back>
      <listOrg type="structures">
        <org type="laboratory" xml:id="struct-182223" status="VALID">
          <idno type="IdRef">177793767</idno>
          <idno type="RNSR">200416333R</idno>
          <idno type="ROR">https://ror.org/01f1amm71</idno>
          <orgName>Laboratoire Traitement du Signal et de l'Image</orgName>
          <orgName type="acronym">LTSI</orgName>
          <date type="start">2012-01-01</date>
          <desc>
            <address>
              <addrLine>Campus Universitaire de Beaulieu - Bât 22 - 35042 Rennes</addrLine>
              <country key="FR"/>
            </address>
            <ref type="url">https://ltsi.univ-rennes.fr</ref>
          </desc>
          <listRelation>
            <relation active="#struct-105160" type="direct"/>
            <relation name="UMR1099 / U1099" active="#struct-303623" type="direct"/>
          </listRelation>
        </org>
        <org type="institution" xml:id="struct-105160" status="VALID">
          <idno type="IdRef">26693823X</idno>
          <idno type="ROR">https://ror.org/015m7wh34</idno>
          <orgName>Université de Rennes</orgName>
          <orgName type="acronym">UR</orgName>
          <desc>
            <address>
              <addrLine>Campus de Beaulieu, 263 avenue Général Leclerc, CS 74205, 35042 RENNES CEDEX</addrLine>
              <country key="FR"/>
            </address>
            <ref type="url">https://www.univ-rennes.fr/</ref>
          </desc>
        </org>
        <org type="institution" xml:id="struct-303623" status="VALID">
          <idno type="IdRef">026388278</idno>
          <idno type="ROR">https://ror.org/02vjkv261</idno>
          <orgName>Institut National de la Santé et de la Recherche Médicale</orgName>
          <orgName type="acronym">INSERM</orgName>
          <desc>
            <address>
              <addrLine>101, rue de Tolbiac, 75013 Paris</addrLine>
              <country key="FR"/>
            </address>
            <ref type="url">http://www.inserm.fr</ref>
          </desc>
        </org>
      </listOrg>
      <listOrg type="projects">
        <org type="anrProject" xml:id="projanr-98242" status="VALID">
          <idno type="anr">ANR-22-PESN-0018</idno>
          <orgName>DIIP-HEART</orgName>
          <desc>Digital integration of Perioperative signals in patients with failing heart &amp; vessels</desc>
          <date type="start">2022</date>
        </org>
      </listOrg>
    </back>
  </text>
</TEI>