1 Ocak 2021 Dergi makalesi Açık Erişim

Al-Saadi, Zaid; Sirintuna, Doganay; Kucukyilmaz, Ayse; Basdogan, Cagatay

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  <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/237110</identifier>
  <creators>
    <creator>
      <creatorName>Al-Saadi, Zaid</creatorName>
      <givenName>Zaid</givenName>
      <familyName>Al-Saadi</familyName>
    </creator>
    <creator>
      <creatorName>Sirintuna, Doganay</creatorName>
      <givenName>Doganay</givenName>
      <familyName>Sirintuna</familyName>
      <affiliation>Koc Univ, Coll Engn, TR-34450 Istanbul, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Kucukyilmaz, Ayse</creatorName>
      <givenName>Ayse</givenName>
      <familyName>Kucukyilmaz</familyName>
      <affiliation>Univ Nottingham, Sch Comp Sci, Nottingham NG8 1BB, England</affiliation>
    </creator>
    <creator>
      <creatorName>Basdogan, Cagatay</creatorName>
      <givenName>Cagatay</givenName>
      <familyName>Basdogan</familyName>
      <affiliation>Koc Univ, Coll Engn, TR-34450 Istanbul, Turkey</affiliation>
    </creator>
  </creators>
  <titles>
    <title>A Novel Haptic Feature Set For The Classification Of Interactive Motor Behaviors In Collaborative Object Transfer</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2021</publicationYear>
  <dates>
    <date dateType="Issued">2021-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Journal article</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/237110</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1109/TOH.2020.3034244</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">Haptics provides a natural and intuitive channel of communication during the interaction of two humans in complex physical tasks, such as joint object transportation. However, despite the utmost importance of touch in physical interactions, the use of haptics is under-represented when developing intelligent systems. This article explores the prominence of haptic data to extract information about underlying interaction patterns within physical human-human interaction (pHHI). We work on a joint object transportation scenario involving two human partners, and show that haptic features, based on force/torque information, suffice to identify human interactive behavior patterns. We categorize the interaction into four discrete behavior classes. These classes describe whether the partners work in harmony or face conflicts while jointly transporting an object through translational or rotational movements. In an experimental study, we collect data from 12 human dyads and verify the salience of haptic features by achieving a correct classification rate over 91% using a Random Forest classifier.</description>
  </descriptions>
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